14th IWNC
PROGRAM OF THE 14th INTERNATIONAL WORKSHOPKSHOP ON NATURAL COMPUTING at TOHOKU UNIVERSITY, SENDAI, JAPAN
January 20-22, 2023
All presentations,talks, and discussions are in Room 115, Global Learning Center, Building A12 on Kawauchi Campus (North) of TohokuUniversity (entrance to A12 is about 50 meters SW (up the hill) from Kawauchi SubwayStation – easy-to-spot a white vending machine with the name KIRIN next to the
entrance). All sessions will be accessible via ZOOM sessions. Please feel free
to share the invitation link with your friends who are interested in the
subject.For those who will participate via ZOOM:
Zoom Meeting Link
https://zoom.us/j/93925762089?pwd=NExRSmhTR3NhQmI3L0dlOHVORlZFUT09
Meeting ID: 939 2576 2089
Passcode: 220105PLEASE FEEL FREE TO SHARE THE PROGRAM, LINK, ETC WITH YOUR FRIENDS AND COLLEAGUES
Friday, January 20, 2023
18:00-20:30 Short popular lectures for Tohoku University students on the subject of the Workshop. Confirmed
lectures:Yasuhiro Suzuki (NagoyaUniversity) “Tactileology, Computing with Tactile Sense”
Katsunobu Imai(Hiroshima University) "Utilization of Cellular Automata"
Martin Robert (Kyoto University) “Links between cellularmetabolism and computation”
Takeshi Koike (Tohoku University)“Questions about Emergence of Intelligence”
Marcin J. Schroeder (TohokuUniversity) “Conventional and Unconventional Computing”
Saturday, January 21,2023
Ø 10:00 - 10:15 Opening
Ø 10:15 - 10:45 Yasuhiro Suzuki (GraduateSchool of Informatics, Nagoya University Japan) ysuzuki@nagoya-u.jp
“Inter-InduceComputation, as a model of Computing with Tactile Sense”
Ø 11:00 -12:00 Shin-ichiro M. Nomura (Tohoku University, Japan) shinichiro.nomura.b5@tohoku.ac.jp INVITEDTALK “Molecular cybernetics: viewpoints from the material side”
Ø 12:15 - 13:30 Lunch Break
Ø 13:30 – 14:30 Kenichi Morita (HiroshimaUniversity, Japan) km@hiroshima-u.ac.jp
INVITED TALK "Time-reversalsymmetries in reversible partitioned cellular automata" Ø 14:45 – 15:45 Yukio-Pegio Gunji (Waseda University, Japan) pegioyukio@gmail.comand Daisuke Uragami (Nihon University) INVITED TALK “Critical computation in the disequilibration between the active and passive computing”
Ø 16:00 – 16:30 Marcin J. Schroeder (IEHETohoku University Sendai Japan) mjs@gl.aiu.ac.jp “Merging Mathematical Models ofInformation for the Digital and Analog Computing”
Ø 16:45 – 17:45 Aaron Sloman (University of Birmingham, UK) a.sloman@bham.ac.uk
INVITED TALK “Recently hatched ideas about hatching andintelligence”
Ø 18:00 – 18:30 Discussion & Reflectionson Topics of the Day
Sunday, January 22, 2023
Ø 8:45 – 9:00 Opening of the Day
Ø 9:00 - 10:00 Michael Levin (AllenDiscovery Center at Tufts University, USA) Michael.Levin@tufts.edu" INVITED TALK“Bioelectrical networks enable navigation of anatomical morphospace in
embryogenesis, regeneration, and cancer"Ø 10:15– 10:45 Masami Hagiya (University of Tokyo, Japan) hagiya@g.ecc.u-tokyo.ac.jp
“GrowingPoint Automata and DNA Computing”
Ø 11:00 – 11:30 Attila Egri-Nagy (Akita International University, Akita, Japan) egri-nagy@aiu.ac.jp “AI, games, and theproblem of scientific realism”
Ø 11:45 –12:15 Martin Robert (Laboratory of Microbial Systems Biology, GraduateSchool of Pharmaceutical Sciences, Kyoto University, Japan) robert.martin.4m@kyoto-u.ac.jp “Metabolism as one instantiation of natural computing”
Ø 12:30 – 13:30 LUNCH BREAK
Ø 13:30 – 14:00 Akika Utsumi1,Toru Moriyama2 (Graduate School of BiomedicalEngineering, Shinshu University, Japan) 21BS202A@shinshu-u.ac.jp1 toru@shinshu-u.ac.jp2 “A study on the ability to regulate inverterfor turn reaction in pill bugs”
Ø 14:15 – 14:45 DavinBrowner (Robotics Laboratory, Royal College of Art, London,UK) davin.browner-conaty@network.rca.ac.uk “Electropolymericelectronics compiler approach to fabrication of ferroelectric memristors with applications in auditory neurotechnologies”
Ø 15:00 – 16:00 Gordana Dodig-Crnkovic(Chalmers University, Sweden) Gordana.dodig-crnkovic@chalmers.se INVITED TALK “Exploring the Connection Between Life, Cognition, and Intelligence
through an Info-computational Approach” Ø 16:15 – 17:15 Andrew Adamatzky (Unconventional Computing Laboratory UWE Bristol, UK) andrew.adamatzky@uwe.ac.uk INVITED TALK "Towards fungal brain: sensing and computing with fungi"Ø 17:30 – 18:30 Discussion on the future directions in the inquiry of natural computing
Ø 18:30 Closing
BOOK OF ABSTRACTS FOR THE 14thINTERNATIONAL WORKSHOP ON NATURAL COMPUTING at TOHOKU UNIVERSITY, SENDAI, JAPAN
January 20-22, 2023ANNOUNCEMENT OF THE WORKSHOP
14th InternationalWorkshop on Natural Computing will be held at Tohoku University in Sendai,
Japan on the weekend Friday through Sunday, January 20-22, 2023. Although the Workshop is planned in principlein the in-person format, we are planning a limited number of presentations to
be delivered by ZOOM for those whose long-distance travel would make
participation impossible.The series of InternationalWorkshops on Natural Computing initiated in 2006 grew up from the original
interest in molecular computing. However, within the years following this
original initiative, the topic of natural computing became one of the main
directions of study in several disciplines. Natural processes or even entire
life started to be considered a form of information processing with
characteristics of computing. On the other hand, information processing in
natural systems became a source of inspiration for innovation in computer
science, artificial intelligence, and engineering. Moreover, computer
simulation became a common tool for the study of nature.Following this general trend ofmutual interactions of disciplines, the 14th International Workshopon Natural Computing continues the already-established tradition of the IWNC
series to devote its sessions to the recent and future developments in
research, practice, philosophical reflection, and creative activity within the
crossroads of nature, computing, information science, cognitive science, the
study of life and culture.The workshops bring together a verywide range of perspectives on natural computing (in its diverse ways of
understanding) from philosophical to scientific ones, to visions of artists.
There is an opportunity to present original and creative contributions without
any restriction by disciplinary divisions or the level of advancement of
research. Contributions from the beginning of the academic or intellectual
career are as welcome as those from its peak.ORGANIZING/PROGRAMCOMMITTEE OF THE 14th IWNC:
(Chair)Marcin J. Schroeder (Tohoku University) <schroeder.marcin.e4@tohoku.ac.jp>
MasamiHagiya (University of Tokyo) <hagiya@g.ecc.u-tokyo.ac.jp>
KatsunobuImai (Hiroshima University) <imai@hiroshima-u.ac.jp>
YasuhiroSuzuki (Nagoya University) <ysuzuki@nagoya-u.jp>
ConfirmedInvited Speakers: Ø Andrew Adamatzky (Unconventional Computing Laboratory UWE Bristol, UK): "Towards fungal brain: sensing and computing with fungi"
Ø Gordana Dodig-Crnkovic(Chalmers University, Sweden): “Exploring the Connection Between Life, Cognition, and Intelligencethrough an Info-computational Approach”
Ø Yukio-Pegio Gunji (Waseda University, Japan): “Critical computation in the disequilibration between the active and passive computing”
Ø Michael Levin (AllenDiscovery Center at Tufts University, USA): "Bioelectrical networks enable
navigation of anatomical morphospace in embryogenesis, regeneration, and
cancer"Ø Kenichi Morita (Hiroshima University,Japan): "Time-reversal symmetries in reversible partitioned cellular
automata"Ø Shin-ichiro M. Nomura (Tohoku University,Japan): “Molecular cybernetics: viewpoints from the materialside”
Ø Aaron Sloman (University of Birmingham, UK): “Recently hatched ideas about hatching and intelligence”
ABSTRACTS
INVITED LECTURES:
1. Towards fungal brains
Andrew Adamatzky
Unconventional Computing Lab, UWE Bristol, UK
Fungi exhibit oscillations of extracellular electrical potentialrecorded via differential electrodes inserted into a substrate colonised by
mycelium or directly into sporocarps. Fungal spiking activity is very similar
to that recorded from central nervous system of humans and animals. Fungi
significantly reduce their electrical activity when placed under general anesthesia,
similarly to what humans do. Thus, we can conclude that fungal mycelium acts as
a brain. Fungal brain is a very slow and very large brain spanning hectares. We
analysed fungal electrical activity using linguistic and information complexity
techniques. We found that distribution of fungal word length matches that of
human languages. We also discovered that language of fungi is more complex
morphologically than human language.***
2. Exploring the Connection Between Life,Cognition, and Intelligence through an Info-Computational Approach
Gordana Dodig-Crnkovic
Chalmers University ofTechnology, Gothenborg, Sweden
&School of Innovation, Design and Engineering, Mälardalen University, Sweden
Gordana.dodig-crnkovic@chalmers.se
Cognition, traditionally thoughtof as a uniquely human ability, has been found to be present in all living
organisms, from single cells to humans. This research investigates cognition
from an info-computational perspective, viewing structures in nature as
information and natural processes as computation, from the perspective of a
cognizing agent.New discoveries in relatedfields, including self-organization, autopoiesis, and evolution on various
levels of organization, have enhanced our understanding of the foundations of
cognition. It has become evident that cognition drives evolution, and evolution
drives cognition in living organisms, a process that is best understood through
the extended evolutionary synthesis.Morphological and morphogeneticcomputation play a vital role in the self-assembly and self-organization of
physical, chemical, and biological agents, leading to the emergence of
cognition. Morphogenesis, the process by which an organism develops from active
matter, is seen as a form of morphological computation. Cells are
information-processing, communicating, learning, and adaptive agents, with
morphogenesis supporting Bayesian inference. The free energy principle and
agency are central to cognition from single cells up.This work is exploring theinterplay between life, cognition, and intelligence through an
info-computational approach. A deeper understanding of the mechanisms of
cognition is important for the advancement of fields such as artificial
intelligence, robotics, and medicine.***
3. Critical computation in the disequilibration between the active and passive computing
Yukio-Pegio GunjiWaseda University, Tokyo, Japan pegioyukio@gmail.com and Daisuke Uragami Nihon University, Tokyo, Japan
While cellular automata synchronously updated can be classified into chaos (Class III), order (Class 1, II) and critical behavior (Class IV), and it was reported that critical behavior can be used for universal computation, Class IV automata are very rare and very specific. If elementary cellular automata are implemented by asynchronously updating equipped with disequilibration between the active and passive updating, most cellular automata which show Class I, II and III behavior if they are synchronously updated show Class IV behavior. We here show this type of cellular automata have criticality in terms of power law distribution, highly efficient and universal computation power, and reveal higher performance in machine learning of the reservoir computing than reservoir computing equipped with class 3 automata.
***
4. Bioelectrical networks enable navigation ofanatomical morphospace in embryogenesis, regeneration, and cancer
MichaelLevin
Allen Discovery Center at Tufts University, USA
Living beings are remarkable self-assemblingassembling computationalcomputational systems, which make the journey from the chemistry and physics of
a quiescent oocyte to the complex metacognitive capacities of humans, and many
variants of cognition in between. In this talk, I will describe our efforts to
understand life as a multi-scale competency architecture, using computational
methods as both tools and metaphors. Analysis of the embryogenesis and
regeneration of complex living forms as a collective intelligence navigating various
problem spaces has enabled interesting advances in basic evolutionary biology
and also applications in biomedicine. I will discuss and show experimental
examples of concepts such as biological reprogrammability, creative
problem-solving machines, and the basal cognition of tissues that are not
brains, and the implications of these ideas across medicine, robotics, and AI.***
5. Time-reversal symmetries inreversible partitioned cellular automata
Kenichi Morita
HiroshimaUniversity
Areversible cellular automaton (RCA) is called `time-reversal symmetric'
(T-symmetric, for short) if its backward evolution is governed by the same
local transition function for the forward evolution. In this study, we
investigate this property using the framework of elementary triangular
partitioned CA (ETPCA), and elementary square partitioned CA (ESPCA). It is
shown that all reversible ETPCAs and about 60 percent of reversible ESPCAs are
T-symmetric under simple transformations on configurations. The transformations
used here are (1) reversing moving directions of all particles, (2) taking a
mirror image of a configuration, (3) 0-1 complementationofeach state, and their compositions. They are somewhat similar to the
CPT-symmetry in physics.Theproved results on T-symmetries are used to find and analyze backward evolution
processes in reversible PCAs. Inparticular, for a given functional module implemented in a reversible PCA,wecan obtain its inverse functional module very easily using its T-symmetry. By
this, designing larger functional objects or reversible machines is simplified.***
6. Molecular cybernetics: viewpoints from thematerial side
Shin-ichiroM. Nomura
Tohoku University, Sendai, Japan
shinichiro.nomura.b5@tohoku.ac.jp
Molecularcybernetics is a fundamental research framework that enables molecular systems
to behave more intelligently and autonomously [1]. In recent years, there have
been ongoing challenges for preparation the desired higher-order structures and
intermolecular interactions by designing the sequence of biological macromolecules
such as DNA, RNA, or proteins, and to realize molecular systems for logical
operations and decision making [2-5]. We have realized prototype molecular robots
that use lipid membrane vesicles as compartments that separate the internal molecules
from the environment [6], and in which sensors, processors, and actuators are
systemized [7-10]. As the next step, molecular cybernetics seeks to realize
information input from environment, storage, learning, output, and deployment
through information transfer between the individual compartments [1]. Specific
challenges include the transfer of sequence information across membranes, the
realization of memory and learning circuits, the precise design and arrangement
of artificial multicellular structures, and the transfer of molecular information
between vesicles. In this presentation, we will introduce the achievements
realized to date, especially information transfer inside and outside vesicles
[11,12] and automated production of artificial multicellular structures [13]
and discuss the prospects for the future.References
[1]S. Murata, T. Toyota, S.-I. M. Nomura, T. Nakakuki, A. Kuzuya, Adv. Funct.
Mater.2022,32, 2201866.
[2]L. M. Adleman, Science 1994, 266, 1021–1024.
[3]K. Sakamoto, H. Gouzu, K. Komiya, D. Kiga, S. Yokoyama, T. Yokomori, M.
Hagiya,Science 2000, 288, 1223–1226.
[4]S. Okumura, G. Gines, N. Lobato-Dauzier, A. Baccouche, R. Deteix, T. Fujii, Y.
Rondelez,A. J. Genot, Nature 2022, 610, 496–501.
[5]I. Kawamata, S.-I. M. Nomura, S. Murata, New Gener. Comput. 2022, DOI
10.1007/s00354-022-00156-4.
[6]M. Hagiya, New Generation Computing 1999, 17, 131–151.
[7]Y. Sato, Y. Hiratsuka, I. Kawamata, S. Murata, S.-I. M. Nomura, Sci Robot 2017,
2,DOI 10.1126/scirobotics.aal3735.
[8]Y. Sato, K. Komiya, I. Kawamata, S. Murata, S.-I. M. Nomura, Chem. Commun.
2019,55, 9084–9087.
[9]S. Murata, A. Konagaya, S. Kobayashi, H. Saito, New Generation 2013.
[10]M. Hagiya, A. Konagaya, S. Kobayashi, H. Saito, S. Murata, Acc. Chem. Res.
2014,47, 1681–1690.
[11]S. Iwabuchi, I. Kawamata, S. Murata, S.-I. M. Nomura, Chem. Commun. 2021,
57,2990–2993.
[12]S. Iwabuchi, S.-I. M. Nomura, Y. Sato, Chembiochem 2022, e202200568.
[13]S.-I. M. Nomura, R. Shimizu, R. J. Archer, G. Hayase, T. Toyota, R. Mayne,
A.Adamatzky, ChemSystemsChem 2022, DOI 10.1002/syst.202200006.
***
7. Recently hatched ideas about hatching andintelligence:
Using verylow energy physics and chemistry at "normal" temperatures in egg-laying vertebrates, with surprising implications for several research fields,possibly including fundamental physics.
AaronSloman
University ofBirmingham, UK
ExtendedAbstract for invited talk at International Workshop on Natural Computing 20-22
Jan 2023 https://www.natural-computing.com/iwnc-wsRecently hatched ideas about hatching and intelligence
https://www.cs.bham.ac.uk/research/projects/cogaff/misc/evo-devo.htmlVery Short Abstract
I'll try to show how hatching processes ineggs of vertebrates have important links with a collection of apparently
unrelated problems in a variety of research and engineering domains, including
philosophy of mathematics, philosophy of mind, metaphysics, artificial
intelligence, theoretical physics, biological evolution, developmental biology,
chemistry, biochemistry, neuroscience, developmental psychology, and especially
the Symbiogenesis theory proposedby Lynn Margulis.Extended Abstract and Notes
I'll try to show how hatching processes in eggs of vertebrates have important
links with a collection of apparently unrelated problems in a variety of
research and engineering domains, including philosophy of mathematics,
philosophy of mind, philosophy of science, metaphysics, artificial
intelligence, theoretical physics, biological evolution, developmental biology,
chemistry, biochemistry, neuroscience, developmental psychology, and especially
the Symbiogenesis theory proposed by LynnMargulis.Metamorphosis in insects, summarised usefullyin https://nhm.org/marvelous-metamorphosis,is also very interesting and closely related, but for now it suits my purposes
to focus on vertebrate egg-laying species: they present important
challenges and (largely unnoticed) clues!The key ideas are also relevant to mammalianreproduction, although that is far more complex than reproduction in eggs
outside the mother, because of rich biochemical interactions between mother and
foetus, before birth, and continuing varieties of influence after birth, in the
case of mammals.Birds that have to keep their helpless hatchedoffspring in the nest to be fed until they have the strength to fly are also
exceptions. This presentation will ignore, or say very little about, such
cases.I suspect that some of the hatching mechanisms andprocesses discussed below challenge current theories about fundamental physics.
I am grateful to theoretical physicist, AnthonyLeggett https://royalsociety.org/people/anthony-leggett-11804/ fornon-committal but encouraging comments relating to this.
(He has not read and is not responsible for any errors in, this document.)Key ideas:
Processes of gene expression producing new biochemical structures, mechanisms
and processes, in organisms of many kinds, have been investigated by many
researchers in many different research and engineering fields, including
biochemical medical engineering. But, as far as I can tell, none of them have
attempted to formulate the specific collection of questions and conjectures
discussed below -- questions about mechanisms that are able to initiate and
help to control increasingly complex construction processes in eggs of
vertebrates during hatching.This process includes biochemicaldisassembly and assembly processes that transform relatively unstructured
chemical biomasses in a new-laid egg into an intricately structured new
vertebrate animal, e.g. a baby chicken, duck, swan, alligator, crocodile,
turtle, python, etc. etc. -- that also possesses unlearnt knowledge about how
to act in the environment.How is that transformation achieved?
Key sub-questions:
How can highlyparallel, multi-layered, constantly branching, chemical processes in an egg produce not only extremely complex, intricately related, physiologicalstructures and mechanisms of many kinds, all required for post-hatching
functioning of the new animal, but also post-hatching species-specific behavioural competences,i.e. abilities to act appropriately (for organisms of that type), in their
environment, e.g. moving around, avoiding obstacles, feeding themselves and in
some cases, but not all, following parents?The point isillustrated by the post-hatching behaviours of avocet chicks in this 35 second
videoclip from a BBC Springwatch programme in June 2021:
https://www.cs.bham.ac.uk/research/projects/cogaff/movies/avocets/avocet-hatchlings.mp4.
The full programme is available on YoutubeIt shows new hatchlings engaged inrich interactions with a complex environment, including walking to a river and
"fishing" for food, all done long before they have had time to train
neural networks for the purpose.Another type of example is shown bysea turtles that fend for themselves after hatching, with no parents to look
after them, in this tutorial video https://www.youtube.com/watch?v=C9VydNhr35YOf course, there are thousands (orbillions?) of different examples of hatching processes that produce both new
bodies and new competences in those bodies, to be found all over this planet.In all the above cases, hatchlingsneed to use fairly complex competences before they have had time, or
opportunity, to acquire the competences by training neural networks (which
don't exist during early phases of hatching and could not be trained within an
egg to control behaviour in an inaccessible environment outside the eggshell!).The only possible source ofcompetences of newly hatched animals is the genetically (biochemically)
controlled in-egg hatching process.(Does anyone know whether any otherother parts of the universe include similar forms of biological reproduction
and evolution? Could evolution of vertebrate animals and/or mathematicians able
to make discoveries about topological or geometric necessity or impossibility
be unique to this planet?)I have the impression that very fewresearchers understand that the vast amount of recent research on
statistics-based neural networks cannot explain ancient human (and some
non-human, e.g. squirrel) abilities to detect and make use of
spatial impossibility or necessity.And few understand Immanuel Kant'spoint in his (Critique of PureReason 1781) implyingthat statistics-based mechanisms cannot explain mathematical discoveries
concerning impossibility and necessity (e.g. in geometry and topology) --
including discoveries that were made centuries before well known ancient
mathematicians such as Pythagoras, Euclid and Archimedes were born, and even
longer before logic-based reasoning mechanisms were invented and used by
humans.Necessity and impossibility are nothigh and low points on a scale of probabilities. They have totally different
origins from probabilities.As Kant noticed, ancient precursorsof such mathematical competences are essential for many non-mathematical
spatial competences. Examples include avoiding obstacles, making tools, moving
complex objects through narrow openings (e.g. a table too wide to fit through a
doorway, but capable of being rotated in 3D space), building nests, and caring
for offspring. (He had other examples.)Crucially, he also realised thatneither impossibility nor necessity can be derived from statistical evidence
supporting probabilities.So, impossibility and necessity --key features of mathematical discoveries in past millennia, and also relevant
to intelligent selection of actions to achieve goals -- cannot be detected
using statistics-based neural network mechanisms, a point that seems not to
have been understood by the vast majority of contemporary researchers working
on natural and artificial neural networks that collect statistical evidence and
derive probabilities!Presumably, those researchers havenot read and understood Kant's claims made in 1781.
Many philosophers, and perhaps otherthinkers, now accept the mistaken, belief (which I first encountered as a
student, around 1958) that Kant's views on mathematical discovery were refuted
by Eddington's observations of a solar eclipse in 1919, confirming Einstein's
claim in his theory of General Relativity that physical spaces are not
necessarily Euclidean.Discussions of that claim usuallyignore the fact that non-Euclidean structures have been commonplace, since long
before Einstein was born, e.g. the surface of a ball, or a kettle, and the
surfaces of most human body-parts.The existence of such non-Euclideanstructures does not refute ancient mathematical discoveries about properties of
Euclidean structures!The ideas presented below providesteps toward a defence of Kant's views on mathematical discovery that nobody
could have thought of two and a half centuries ago.Is there related work doneelsewhere?
I would be interested to hear about any researchers attempting to explain the
combined, detailed, problems of parallel construction, within an egg, of a
very broad and varied, intricately interrelated, collection of physiological
structures, while also producing significant species-specific competences
that are required soon after hatching, for interacting appropriately with
structures in the environment -- including abilities to
detect impossibilities, or to perform actions with useful necessary
consequences.There are many researchers workingon self-organising, chemistry-based mechanisms, e.g. in slime moulds, but I
have not encountered any that meet the above requirements.The work of Mike Levin at Tufts University (another invited speaker atthis conference) is particularly impressive, but the work I have seen also
addresses only a subset of the problems. As far as I know he has not discussed
mechanisms that are able to detect impossibility or necessity (which are not
degrees of probability) or tried to explain the parallel assembly of a
huge variety of different but intricately interrelated physiological
structures.I apologise to any researchers whosework does address all the issues mentioned here. I'll be pleased to add
references to such work in the online version of this document.
(Email a.sloman-At-bham.ac.uk.)Competences of new hatchlings
My attempts to link these old investigations to hatching processes in eggs of
vertebrates (extending previous research with students and colleagues in Philosophy/AI/Cognitive
Science since 1959) began in 2020, triggered by reflecting (for the first time)
on the well known (but widely ignored?) fact that there are many species of
vertebrate hatchlings that emerge from eggs, not only possessing bodies that contain
a huge variety of extremely intricately interconnected internal physiological
substructures and mechanisms, but also possessing important species-specific
spatial competences combining complex perception and action mechanisms, that
are used before the new hatchling has had time or opportunity to train neural
networks after hatching.These mechanisms are used inperforming tasks such as breaking out of the eggshell, following a parent, or
going to food and eating it, all done without prior learning or training, as
illustrated by the 35 second avocet video extract above,showing new hatchlings engaged in rich interactions with a complex environment
including walking to a river and "fishing" for food.There seems to be evidence ofsimilar precociality in hatchlings of a long extinct dinosaur species,
referenced below.Do mechanisms underpinningcompetences of new hatchlings challenge current physics?
The abilities of such hatchlings must somehow be produced by (hitherto
unnoticed??) biochemical hatching processes in eggs. How?My (partial, tentative, and hard todigest(!)) answer outlined below attempts to link products of processes on many
different time scales within and across species, produced by branching and
converging evolutionary histories.The answer seems (to me) tochallenge current fundamental physical theories (as has happened repeatedly in
the history of physics), though my original aim was
to use fundamental physical theories (with expert help from
theoretical physicists), not to challenge current physics.If it turns out that physics needs anew revolution, in order to explain hatching processes in eggs, it won't be the
first revolution in physics triggered by new empirical discoveries. For
example, the discovery of magnetism, centuries ago, and the discovery (many
centuries later) of connections between magnetism and electricity, led (via
Oersted, Ampere, Faraday, Maxwell, and others) to major changes in fundamental
physical theories, as well as many engineering applications of electromagnetic
mechanisms.Could understanding hatchingprocesses also lead to currently unexpected (unbelievable?) new developments in
science and engineering?Relevant well-known facts
There are many different egg-laying vertebrate species, including chickens,
avocets, alligators, turtles, pythons, etc., whose young emerge from eggs with
very different physical forms, all possessing intricately interrelated general
and species-specific physiological structures, and a collection of
species-specific behavioural competences available after hatching, without
having to be learnt by acting in the environment.Less obviously, hatching processesdepend on species-specific chemical assembly competences used inside eggs
during hatching -- competences with their own developmental and evolutionary
histories.Hatching processes in the eggs ofsuch species both:
-- transform the original relatively small variety of chemicals in new-laideggs into a much larger variety of chemicals used in multiple, intricately
interrelated, body-parts of the new hatchling, with many different functions.and also
-- construct mechanisms that provide a varietyof post-hatching spatial competences, used without requiring any training.E.g. new hatchlings of many speciescan perceive objects in the environment, select goals, plan and execute
suitable actions, including following a parent, moving toward, or avoiding,
objects in the environment; and feeding themselves.- during hatching there's arepeatedly branching variety of new physiological substructures, requiring a
repeatedly branching variety of new construction-control mechanisms for
constructing new construction-control mechanisms. Earlier ancestors of such
species would have had fewer developmental phases and would have needed fewer
construction-control processes during hatching.Note about invertebrate species:
Related phenomena occur in insects that start life as grubs that grow by
feeding themselves then produce cocoons in which processes of metamorphosis
occur that transform the grubs into adults that have both completely new
physiological structures (e.g. including wings) and new behavioural
competences, e.g. flying, feeding in a new way and mating.The insect examples may laterprovide evidence that can suggest or test answers to my questions about
processes in vertebrate eggs, but they will not be discussed further in this
introduction.Main conjecture
There must be a multi-layered answerto this question:
How can so much extremely complexinternal rearrangement of physical matter happen inside the eggshell of a
developing vertebrate animal, starting with a single fertilised cell surrounded
by a relatively small number of chemical substances separated by membranes in
the egg?Discussion and questions
The above question is concerned withproduction of physical structures and mechanisms inside eggs. There are also
questions about how behavioural competences in newly hatched animals are
produced.How can chemical processes in eggsalso produce competent new animals with a combination of enormously complex and
varied species-specific internal physiological structures and processes as well
as unlearnt behavioural competences?
(Like the competences of the avocets, referenced above.)The main idea proposed here is thatthe abilities of biochemical processes in eggs to produce post-hatching
behaviour, in addition to assembling increasingly complex physical structures
within the egg, is a recent extension of an evolutionarily older class of
biochemical mechanisms that contribute to development of additional
physiological complexity in the hatching process while they are controlling
physical assembly processes by rearranging chemical substances within the egg.The older mechanisms were alsopresumably once relatively recent extensions of even older classes of
mechanisms and competences inherited via backward branching routes (coming from
male and female parents, and their mail and female parents, etc.)Biological evolution is not andcannot be a continuous process in any species that uses existing members to
produce new members of the species.Moreover, insofar as the processes of developmentin an egg involve removal and formation of chemical bonds they also cannot be
continuous. This is explicit in Schrödinger's discussion of reproductive
processes in What is life? (1944).What I am now suggesting is that abilities ofchemical processes in eggs to produce competences for used by an
animal after hatching, are later developments of much older abilities
of chemical processes occurring during a particular phase of assembly
inside the egg corresponding to a certain period in its evolution, to
produce the assembly control mechanisms required for the next stage of
development inside the egg, i.e. a developmental stage that is a product of
more recent evolutionary processes.So each phase of assembly produces or modifies newphysiological structures and also creates control mechanisms required for
assembly of the next phase of development, corresponding to a more recent
evolutionary development.The above line of thought leads to the conjecturethat the mechanisms producing competent post-hatching behaviours are relatively
recent evolutionary products, following earlier evolutionary products whose
behaviours (i.e. separating and re-using components of molecules provided in
the egg by the mother) occur during, not after, hatching, whereas the latest
evolutionary products produce behaviours after hatching.There are also difficult questions about howevolutionary processes were able to get the required information into the
chemical structures in a newly formed egg.[After I asked myself that question, an internet searchled me to this surprising answer: https://www.ucdavis.edu/food/news/study-challenges-evolutionary-theory-dna-mutations-are-random (byEmily C. Dooley).
My main claim is that answers to these questions,i.e. explanations of the evolutionary and developmental phenomena relevant to
assembly of new structures in an egg, depend on multi-stage processes of
development in eggs, using increasingly complex biochemical developmental
control mechanisms specific to eggs of that species.The in-egg mechanisms "bootstrap"construction of both
-- increasinglycomplex physiological structures in eggs, corresponding to different stages in
evolution of the species,and also construction of
-- increasinglycomplex forms of new virtual (non-space-occupying) machinery, that
control additional intricate, multi-strand, highly parallel, chemical assembly
processes inside the egg.As a result those in-egg processesare also able to produce mechanisms that control species-specific post-hatching
behavioural competences, illustrated by the post-hatching behaviours of young
avocets above.How is all that possible?
An incomplete answer is sketched inmy talks and online notes on this topic, involving (among other features)
hypothesized use of a previously unnoticed [*], parallel,branching, growing collection of increasingly species-specific in-egg
"Maxwell demons", implemented using conjectured increasingly complex
multi-layered forms of virtual machinery operating within the egg, but without
occupying physical space in the egg, since no spare space is available![*]. Ifanyone knows of related work on hatching mechanisms, I'll be grateful for
information. [Contact: a.sloman AT bham.ac.uk]Could all that be achievable duringhatching by using increasingly large collections of simultaneously
active eletromagnetic signals, some of which trigger production of both
new physiological structures and also new control machinery required for later
stages of assembly?What mechanisms could enable increasinglymany concurrently active construction/assembly mechanisms to operate in
parallel in the same small space (i.e. inside the hatching egg), without
seriously interfering with one another, during normal development -- though
sometimes things go wrong, producing deformities, conjoined twins etc., as
reported in
https://www.thepoultrysite.com/articles/chicken-embryo-malpositions-and-deformitiesIn short: I conjecture thatsuccessive collections of virtual machinery in the egg control constructions in
different developmental stages during hatching, by controlling chemical
processes that produce new, increasingly complex,
species-specific physiological structures, and also controlling processes
that produce the next level, species-specific, more recently
evolved, successor control machinery, i.e. more recently evolved (virtual)
assembly demons!(Compare Levin's work.)
These ideas are crudely depicted ina complex diagram whose explanation will be an important part of the talk:
https://www.cs.bham.ac.uk/~axs/fig/evo-devo/evo-devo-final.jpg
(possibly modified before the talk).
Also linked in the full version of this document below.<="" a="">Possibleimplications of these ideas
The conjectured mechanisms, including a great deal of simultaneous more or less
coordinated "action at a distance" within the egg (performing much
more complex sorting and construction tasks than Maxwell's demon), may point to
gaps in current fundamental physical theories, in addition to the need for
important revisions of theories in philosophy of mind, philosophy of
mathematics, philosophy of science, psychology, neuroscience, theoretical
biology, and AI.<=""a="">A comparison with the following may be useful:
Increasingly sophisticated forms of virtual machinery have been developed by
human designers during the last half century, especially since the advent of
the internet and applications such as online banking, online distributed
databases of information, online reservation systems, and applications such as
email, discussion support mechanisms (e.g. Zoom), online games, etc.<=""a="">Instead of the kinds of digital computing technology used by
human engineers to implement virtual machines, ancient processes of biological
evolution anticipated such achievements for use in far more complex and
intricate biological control processes, on a far smaller physical scale, using
biochemical mechanisms.<=""a="">This is related to some of the claims made by Lynn Margulis,
referenced below,regarding the role of symbiogenesis in the history of this planet.
Compare Shubin et.al.(1997)Limitations of digital technology
Digital technology would be incapable of replicating these processes, in which-- very complex molecularreorganisation mechanisms are used, decomposing a relatively small variety of
types of molecule in new-laid eggs, and using the products of decomposition in
construction of many new materials with a variety of different sorts of
physical properties and physiological functions,-- the processes are controlled(e.g. in hatching eggs) in accordance with a very detailed set of species-specific
requirements for a fully functional biological organism of a particular sort,
e.g. alligator, chicken, swan, turtle, python, etc.,-- the processes occur in very muchsmaller spaces than assembly processes in human designed factories,
-- the process products varyenormously, within individual organisms, including bones with different sizes,
shapes and locations in the body, muscles, nerve fibres, various brain
structures, digestive mechanisms, blood vessels, blood, glands, chemicals produced
by glands (different sorts of hormones), lungs, skin, scales, feathers, and
other outer coverings, and various bodily openings, e.g. for feeding,
breathing, excreting etc. after hatching, and different sex organs for males
and females,-- whereas components ofhuman-designed machines are typically manufactured separately then brought
together (e.g. on an assembly line) by humans or specialised assembly robots,
many components of a new creature formed in an egg are created in parallel in
roughly their required spatial relations, so that once started they can grow
together with rates of growth of various components varying according to
required later spatial relationships.-- construction of products ofearlier phases of evolution will normally begin during earlier phases of
hatching, in parallel with required construction control mechanisms.and
-- apart from maintenance oftemperature and protection from external disturbances (in cases where parents
are involved in hatching), there is very little intervention or control by
parents or other external objects.Some implications
The above summary implies that eggs (of vertebrate species, and others not
discussed here) do not only produce the very complex physical products that
emerge after hatching, i.e. animals with a large variety of parts with
different structures and functions:They also produce the increasinglycomplex and increasingly differentiated control mechanisms required for
producing all that complexity and diversity during the hatching process.That includes producing increasinglypowerful, increasingly varied, bootstrapping processes, including bootstrapping
processes for producing more complex and functionally differentiated,
bootstrapping processes required during later stages of hatching.I am not claiming that ontogenesisreplicates phylogenesis: individual organisms developing in an egg do not go
through the developmental stages of their ancestors. They don't pass through
the adult forms of all their ancestors.However the mechanisms ofontogenesis (mechanisms controlling assembly of parts of a new organism
using available chemical resources) replicate, at least partially, the
evolution of mechanisms controlling assembly of parts! This claim is presented
graphically in a complex (over-complex?) diagram available in the full version of this document.During the hatching process, both molecularreorganisation processes and mechanisms controlling molecular reorganisation,
grow increasingly complex and increasingly diverse, producing increasingly
varied physical materials needed in different parts of the developing organism,
with increasing amounts of physical parallelism, as hatching proceeds and the
foetus becomes more highly differentiated.***
CONTRIBUTED PRESENTATIONS:
1. Electropolymeric electronics compiler approach tofabrication of ferroelectric memristors with applications in auditory
neurotechnologiesDavin Browner
PhD candidate, Robotics Laboratory, Royal Collegeof Art, London, UK
davin.browner-conaty@network.rca.ac.uk
Auditoryneurotechnology development focuses on the modelling, augmentation and
enhancement of human hearing and in the development of bio-inspired machine
audition methods. Spike-enabled auditory neurotechnologies that make use of
spiking neural networks (SNNs) in combination with acoustic processing
circuitry could be utilised in a wide range of devices for human-interventional
medicine and in novel sensory technologies for neurorobotic and neuroprosthetic
applications [1].Auditoryneurotechnologies where learning methods are based on the physics of memristive
SNNs (MemSNNs) may offer the promise of lower power Artificial Neural Networks
(ANNs) via resistive memory and switching phenomena [2]. However, existing
methods for memristor fabrication are difficult to implement in durable
polymer-based substrates and do not have suitable biocompatibility or acoustic impedance
matching profiles for integration into auditory neurotechnologies. More
generally, many of the resistive switching methods in the literature rely on
phenomena with significant cycle-to-cycle and device-to-device stochastic
switching characteristics (e.g., phase change, ion migration, conductive filament
formation, etc) that complicate hardware implementation and device modeling.Ferroelectric polymer memristorswith good biocompatibility and acoustic impedance matching profiles would be
beneficial for development of MemSNNs for auditory neurotechnologies [3]. In
general, ferroelectric memristors are excellent candidates for auditory
learning applications due to their cycle-to-cycle endurance based on continuous
ferroelectric polarisation, i.e., the “ferroelectric plasticity” that can be obtained
by regulating the amplitude or duration of the applied voltage pulses. The two-terminal
type ferroelectric artificial synapses, which include memristor based devices,
consist of two electrodes that are separated by a ferroelectric film. When a
presynaptic signal is applied to one electrode, an update of the conductance is
generated accordingly, and the synaptic weight can be readout from the other
electrode. In this way, spike signals are transferred from the pre- synaptic
terminal to the postsynaptic one. Ferroelectric spike-enabled memristors also
benefit from potential multi-functionality such as concurrent piezoelectric,
pyroelectric, and/or multiferroic phenomena.In terms offabrication, inorganic ferroelectric memristors require procedures that are
highly sensitive to initial conditions such epitaxial growth and complex
crystal growth optimisations such as use of specific substrates for lattice
matching. In contrast, ferroelectric polymers can easily be dissolved in an
organic solution and directly printed onto flexible substrates. This means that
their easy processing, low cost, and versatility offer feasible solutions for
large scale synaptic design and network formation while also having excellent
properties for use in bio-informational interfaces such as those required in
auditory learning devices due to their biocompatibility and low acoustic
impedance.Despite thesegeneral advantages, the optimal methods for fabrication of ferroelectric
memristors for neuromorphic hardware based on polymers is not established.
Electropolymeric deposition could provide several advantages in terms of
fabrication based on polymers due to bench-top scale fab, rapid speed of deposition,
low cost, and use of flexible and soft substrates. Compared to methods such as
spin coating and screen printing the technique could allow for control over
thickness and resulting conductivity profiles. Electrical control of these
properties would aid in fine tuning of programmable resistance values and
intervals between high-resistance and low resistance states, emulation of
synaptic functionality evidenced by the cycle-to-cycle hysteresis loops of the
resulting polymeric electrode-ferroelectric-electrode (EFE) structure.Apolymeric memristor “compiler” approach to fabrication of memristors is
developed and implemented based on the respective EFE structure via
electropolymeric deposition of the ferroelectric resistive switching layer.
Here, “compiler” is referred to as a method to assemble analogue ferroelectric
memristive elements via potentiostatic control of deposition of alternating EFE
layers. The implemented system uses a silver coated working electrode,
silver/silver chloride reference electrode, and steel wire counter electrode in
the potentiostatic experiment. The procedure is simple. First, a ferroelectric
resistive switching layer material based on an organometallic glycinate complex
is deposited onto the conductive substrate via electropolymeric deposition.
Then, a PEDOT: PSS top electrode layer is deposited on top of the ferroelectric
layer matching the geometry of the conductive substrate and allowing for
electrical connection.Theferroelectric response of the 3D deposited structure has implications for
design methods in auditory neurotechnologies with the potential for more
economical fabrication of devices such as artificial cochleas, hair cells, and
other neuroprosthetics. In addition, the ferroelectric and piezoelectric
response of the metal glycinate complex suggests its existence in biopolymers
such as elastin and collagen [5]. Opening up the potential for devices that
match the biochemistry and acoustic impedance of the skin of the individual.
Finally, novel methods for acoustic sensing in neurorobotic applications could
be based on these properties.Keywords: ferroelectricmemristors, memristive auditory neurotechnologies, fabrication methods, machine
audition.REFERENCES
[1] Goodman,D. and Brette, R., 2010. Learning to localise sounds with spiking neural
networks.Advancesin Neural Information Processing Systems, 23.
[2] Wu,X., Dang, B., Wang, H., Wu, X. and Yang, Y., 2022. Spike-Enabled Audio Learning
in MultilevelSynaptic MemristorArray-Based Spiking Neural Network. Advanced Intelligent Systems, 4(3),p.2100151
[3] Tian,B., Liu, L., Yan, M., Wang, J., Zhao, Q., Zhong, N., Xiang, P., Sun, L., Peng,
H., Shen, H. and Lin,T., 2019. A robustartificial synapse based on organic ferroelectric polymer. AdvancedElectronic
Materials, 5(1),p.1800600.
[4] Niu,X., Tian, B., Zhu, Q., Dkhil, B. and Duan, C., 2022. Ferroelectric polymers for
neuromorphiccomputing. AppliedPhysics Reviews, 9(2), p.021309.
[5] Liu,Y., Cai, H.L., Zelisko, M., Wang, Y., Sun, J., Yan, F., Ma, F., Wang, P., Chen,
Q.N., Zheng, H. andMeng, X., 2014.Ferroelectric switching of elastin. Proceedings of the National Academy of
Sciences, 111(27),pp.E2780-E2786.***
2. AI,games, and the problem of scientific realism
AttilaEgri-Nagy
Akita International University, Akita, Japan
egri-nagy@aiu.ac.jpHow can we learn from superhuman black box AIs? We assume thatthe best way is to use them as an unlimited source of experiments. In other
words, a human user should take the role of a scientist to acquire knowledge:
form hypotheses, and test them with AIs. In the traditional application domain
of board games, a human player should devise a plan, explaining why a chosen
move is good, and then use the machine evaluation to see any possible faults.Treating the human-AI relationship as a scientific situationbrings in all the philosophical issues of science itself. Here we will discuss
the problem of scientific realism, the question of whether the universe studied
by science exists or not. In our analogy, this question has some curious twists.
The explored universe, the complete game tree, does exist. However, in its
totality, it is still an unobservable entity. The obstacle is computational
complexity. In this talk, we will investigate this epistemological issue.***
3. GrowingPoint Automata and DNA Computing
MasamiHagiya
University of Tokyo, Japan
We propose acomputational model in which a network around the nodes called ports is formed
with fibers elongated by the extension and branching of their growing points,
and various computations in the network (such as path formation, circuit
generation, matching, etc.) are realized by the signals transmitted along the
fibers. Growing points and ports havestates that are changed depending on the states of neighboring growing points
and ports. Since the model featuresgrowing points that are elongated according to their states, it is named
growing point automata (GPA) after the growing point language (GPL) proposed in
the study of amorphous computing. Inthis talk, we first give the simple model of growing point automata with an
example of path formation between ports. We then refine this simple model by taking transmission of signals alongfibers into account. We show that thereexists a weak bisimulation between the simple and refined models of path
formation. Finally, we discuss thepossibility of implementing the refined model with DNA molecules. We mainly examine self-assembly of DNA tiles,including so called active tiles that can change their states upon assembly.***
4. Metabolism as one instantiation ofnatural computing
MartinRobert
Laboratoryof Microbial Systems Biology, Graduate School of Pharmaceutical Sciences,
KyotoUniversity, Japan
robert.martin.4m@kyoto-u.ac.jp
Metabolism can be definedas the network of cellular biochemical reactions at the core of mass and energy
exchange in living cells and organisms. One of its important role is the
maintenance of cellular coherence over time and growth. This is achieved by
continuous uptake of nutrients (inputs), their processing through the cellular
metabolic network and resulting in outputs of biomass, energy and waste that
allow to accomplish the objective of cellular maintenance and growth. It thus
represents a central element of cellular natural computing encoded in the form
of biochemical reactions. In this presentation I would like to introduce some
of the important concepts of metabolism that connect to natural computing.
There are interesting examples of optimization in metabolism that appear
conserved in different types of cells from bacteria, stem cells, cancer cells
or brain cells, that consume energy at a high rate. Bacterial biofilms may
provide a simple model to investigate this type of metabolic economy and the
management of shared resources in cellular communities and the resulting
conflicts. These apparent universal and sometimes paradoxical metabolic
responses provide some insight on a cellular economy related to natural
computing that needs to be further appreciated and investigated.***
5. Merging Mathematical Models ofInformation for the Digital and Analog Computing
MarcinJ. Schroeder
IEHE Tohoku University Sendai Japan
The distinction between analog anddigital information is understood as similar to the distinction between the
state of a physical system and observables. The paper presents a formalism based on closure spaces overarching both types of information and merging conceptual frames of diverse theories such as probability, quantum theory of physics, logic, and modal logics.The most popular distinction between digital and analog computing introduced by von Neumann is
based on the difference between the symbolic, digital, and discrete
representation of numbers and their apparently continuous representation as
magnitudes characterizing the states of physical objects. In reality, although
this distinction is highly intuitive and seems to reflect objective differences
between the forms of information, it is purely conventional. The functioning of
all computing devices involves the manipulation of the physical states of their
operating systems and at the same time, the digital representation of numbers
is achieved by a conventional discretization of continuous magnitudes.In this paper, I am usingthe distinction between analog and digital information and computing that I
introduced in my earlier work in which the difference between analog and
digital information is similar to the difference between the concepts of
physics characterizing physical systems by physical states (analog) and
observables (digital). This distinction in physics acquired fundamental
importance with the rise of quantum mechanics but was already present earlier.
I wrote “similar” because essentially identical distinctions can be identified
elsewhere. For instance, the foundations of probability theory can be built
starting from the concept of a family of events understood as measurable
subsets of an outcome space and proceeding to random variables, or
alternatively starting from an appropriate algebraic structure of random
variables and proceeding to special class of random variables that can be
interpreted as characteristic functions for subsets of an outcome set
corresponding to events.The depth of thedistinctions in both quantum theory and in probability theory is rarely
recognized, at least not in an open way. In quantum theory, the issues are
hidden for instance by the use of ad hoc terminology of “hidden variables”
(that sounds better than the oxymoron “unobservable observables”). In
probability theory, the standard trick is to focus on just two special cases of
discrete and continuous random variables while excluding anything else that
causes trouble. Probably the closest to an honest denunciation of the forgotten
problems was the series of the 1998 Turin Lectures by Gian-Carlo Rota “Twelve
Problems in Probability No One Likes to Bring Up.”Rota’s lectures addressednot only issues within probability theory but also in the study of information.
In particular, Rota addressed the issue of the formulation of the orthodox
information theory derived from probability theory while it should precede
probability. This concern was not new as it was already voiced by Kolmogorov a
long time ago when he proposed his solution in the form of a description of
algorithmic complexity. Kolmogorov’s solution did not bring a sufficiently
general solution and Rota directed the future inquiry toward a new logic of
information in terms of the lattice of partitions.Quantum computing becamethe hottest topic of this century but it seems that here too the carriage was
placed in front of the horse. The usual approach is to study quantum computers
considered as a special case of a quantum system and quantum information is
just an engineering concept necessary for the use of such computing devices.
With the increasing role of information as the most fundamental physical
concept as promoted by Rolf Landauer (“Information is Physical”) and John
Archibald Wheeler (“It From Bit”) quantum theory should be derivable from
quantum information theory.A closer look at theformalisms involved in quantum and probability theories brings into focus
another similar type of formalism developed in semantic inquiries of modal
logics based on the idea of possible worlds (initiated by Rudolf Carnap but
already considered by Leibniz), in particular in the frames of Kripke Semantic.
The need for a unifying formalism becomes more and more clear.This paper is an attemptto use my earlier published version of a theory of information to develop an
overarching formalism for information in which all formalisms mentioned above
are special instances. Its conceptual framework is based on the theory of
closure spaces.An information systemspecifying the type of information is a closure space. In this study, there is
no need to restrict this concept by additional conditions unless we proceed to
its application in one of its specific applications. Thus, information can be
of the geometric, topological, logical, or physical type associated with
additional defining conditions. However, here we want to consider a general
formalism. The logic of such a general information system is a complete lattice
of closed subsets of the information system. At this point, it is important to
indicate that the term “logic” has here a much more general meaning than usual
which only in the case of linguistic or probabilistic information systems can
be identified with the familiar Boolean lattice defined by the connectives
between propositions of some language. The less conventional use of this term
consistent with the approach of this paper can be found in quantum logics
defined on the closed subspaces of a Hilbert space (or alternatively on the
projectors on these subspaces) or in Rota’s logic of information identified
with lattices of partitions.The instances of theinformation within an information system are filters (sometimes called dual
ideals) defined on the lattice of closed subsets (the logic of the information
system). Ultrafilters, principal filters, and prime filters characterize
special types of information. Since filters representing instances of the
information are defined on logics that are not necessarily Boolean lattices,
and the theory of filters is typically studied in this particular context (e.g.
Stone Theorem) it is important to be aware of the ramifications of the theory
of filters when we transcend the Boolean context. For instance, ultrafilters
are not necessarily prime filters anymore, which is a fact that frequently
confuses physicists in discussing the question of hidden variables.The formalism based onfilters reflects structural characteristics of information and filters
represent a state of some universe of inquiry (quite frequently simply called
“possible worlds”). Information defined or characterized as filters can be
identified as analog type. However, we have an alternative tool for inquiry of
information referring to observed numerical characteristics associated with
digital type. Here we have s-fields of subsets and measures defined onthem. The measures can be arbitrary, associated with magnitudes characterizing
the objects of inquiry, can be restricted to probability type, or further
restricted to binary logical valuations. In each case, we can construct a
corresponding lattice that can be interpreted as a logic of information.
Furthermore, we can distinguish filters representing instances of information.Finally, we can establishthe relationships between the analog and digital descriptions of information.
These relationships are complex and they heavily depend on the specifics of
information systems. In general, the closest and simplest relationships in the
Boolean type of information systems become more complex and ramified when their
logics are unconventional.Thispaper is about information and its analog and digital forms. However, it
contains as a byproduct some explanations of exotic features (from the point of
view of Boolean logic) of quantum information. For instance, some controversies
in the discussion of the so-called hidden variables can be resolved by
clarifying confusion caused by the import of our common-sense concepts to the
study of quantum theory. The issue of the unavoidable incompleteness of the
quantum-theoretical description of reality can be resolved not by a
demonstration of the absence of hidden variables but rather by using the simple
lattice-theoretical basic fact that a distributive lattice cannot have a
non-distributive sublattice or in other words, we cannot injectively extend a
non-distributive lattice to distributive one.***
6. Inter-InduceComputation, as a model of Computing with Tactile Sense
YasuhiroSuzuki
Graduate School of Informatics, Nagoya University Japan
Tactile communication isa typical interaction in nature. Not only among animals such as humans but also
in molecules, and cells, no matter how it is between living systems or between
substances, it plays a crucial role in information processing.Herewe define "information processing" as computing with an algorithm and
its algorithm as a sequence of instructions. So, algorithms are not only for
computers; even brushing teeth has its algorithm; putting on teeth paste on the
brush, then brushing teeth, and finally rinsing off bubbles with water. We can
change this sequence; for example, rinse off the teeth, then put on teeth paste
and brush; every instruction is equal to an instruction in the former sequence,
but the "result of computation" is different. We call changing a
sequence "programming.”There are full ofalgorithms in nature; a sequence of glycans controls interactions between
influenza viruses and cells, a sequence of DNA / RNA processing proteins
compose living systems. And so on. It is essential that almost all the
information processing is performed by tactile communications; glycan, DNA, or
RNA does not have any "nerve systems" to recognize, such as visual or
auditorial sense. All these substances use tactile communication to recognize
the molecule's shape and process information.The significantcharacteristic of tactile communication is the bi-directionality of
interaction; touching something is simultaneous with being touched by it. In
nature, many tactile communications are composed of multi-agents. Mostly, these
agents have different "aims" to communicate; for example, the aim of
the influenzas virus is the infection of a cell, and the aim of a cell
communicating with the virus is preventing its infection.Theycompute with the algorithm of the sequence of glycans; this computing is
different from ordinal computing problems such as solving a maze or sorting
numbers. The goal of computing is to induce communicating agents to an
"ideal state," such as infection to a cell or repelling an infectious
virus. We call such computing with bidirectional interactions as Inter-Induce
Computing, IIC. We propose a framework of IIC and show some preliminary
results.***
7. A study on theability to regulate inverter for turn reaction in pill bugs
AkikaUtsumi, Toru Moriyama
Graduate School of Biomedical Engineering, ShinshuUniversity, Japan
21BS202A@shinshu-u.ac.jp toru@shinshu-u.ac.jp
Pill bug is an arthropodof about 1 cm in length that lives under fallen leaves. When the experimenter
gives the animal two T-mazes in succession, it turns alternately left and right
with a probability as high as about 80%. It is thought that pill bugs are
equipped with inverters for turning. The success rate of this alternating turn
decreases as the distance between the intersection of the two T-mazes (usually
5-10 cm) is increased, reaching about 50% at 16 cm (Iwata & Watanabe,
1957). When a pill bug equipped with these properties for turning was given
approximately 2,000 consecutive T-maze trials, it was observed to regulate the
number of alternating turns in a continuous manner (Shokaku et al, 2020). This
animal is thought to have a neural circuit that regulates inverter for turning.
To explore new properties of this neural circuit, we conducted experiments at
distances of 16 and 30 cm between maze intersections to investigate how the
pill bug adjusts the inverter when memory of prior turns is lost. The results
of the analysis of the experimental data will be presented at the workshop.13th International Workshop on Natural Computing (IWNC)
@IS4SI 2021
https://summit-2021.is4si.orgFRIDAY, September 17,
4:00-12:30 UTC
IS4SI 2021
The 2021 Summit of the International Society for
the Study of Information
The series of International Workshops on Natural Computing initiated in 2006 grew up from the original interest in molecular computing. However, within the years following this original initiative the topic of natural computing became one of main directions of study in several disciplines. Natural processes or even entire life started to be considered a form of information processing with characteristics of computing. On the other hand, information processing in natural systems became a source of inspiration for innovation in computer science, artificial intelligence and engineering. Moreover, computer simulation became a common tool for the study of nature.
The plan for the Workshop was cancelled in 2020 due to the global outbreak of the new coronavirus. Since it is difficult to predict the future conditions the Workshop is planned in the online format along with the cluster of other conferences of the 2021 IS4SI Summit. This will be a unique opportunity to engage in the interaction and discussion with participants of multiple conferences of the Summit.
Following this general trend of mutual interactions of disciplines, the 13th International Workshop on Natural Computing continues already established tradition of the IWNC series to devote its sessions to the recent and future developments in research, practice, philosophical reflection and creative activity within the crossroads of nature, computing, information science, cognitive science, study of life and culture.
The 13th International Workshop on Natural Computing will be associated with the symposium on Morphological, Natural, Analog and Other Unconventional Forms of Computing for Cognition and Intelligence, which has its own tradition within the Summits of IS4SI.
The intention of the 13th International Workshop on Natural Computing is to bring together a very wide range of perspectives from philosophical to scientific ones, to visions of artists. There will be an opportunity to present original and creative contributions without any restriction by disciplinary divisions or the level of advancement of research. Contributions from the beginning of the academic or intellectual career are as welcome as those from its peak.PAST WORKSHOPS IN THE IWNC SERIES:
1st, Dec 14-15, 2006 : University of West-England, Bristol, UK
2nd, Dec 10-13, 2007 : Nagoya University, Nagoya, Japan
3rd, Sept. 23, 2008 : Yokohama National University, Yokohama, Japan
4th, Spet, 23-19, 2009 ; Himeji International Exchange Center, Japan
5th, Sept, 21, 2010 ; Ascoli Piceno, in ACRI2010, Italy
Mar, 15-16, 2011; as "Winter School of Hakodate", Future University Hakodate, Japan
6th, Mar, 28-30, 2012; Tokyo University, Tokyo, Japan
7th, Mar, 20-22, 2013; Tokyo University, Tokyo, Japan
8th, Mar, 18-19, 2014; YMCA, Hiroshima, Hiroshima, Japan9th, Mar. 15, 2015; Tokyo University, Tokyo, Japan
10th, May 14-15, 2016; Akita International University, Akita, Japan
11th, May 13-14, 2017, Akita International University, Akita, Japan
12th, May 26-27, 2018, Akita International University, Akita, Japan
ORGANIZING COMMITTEE:
Marcin J. Schroeder (Tohoku University, Japan) <mjs@gl.aiu.ac.jp>
Masami Hagiya (Tokyo University, Japan) <hagiya@is.s.u-tokyo.ac.jp>
Yasuhiro Suzuki (Nagoya University, Japan) <ysuzuki@nagoya-u.jp>
Gordana Dodig-Crnkovic (Chalmers University, Sweden) <gordana.dodig-crnkovic@chalmers.se>
PLEASE FORWARD THIS ANNOUNCEMENT TO ANYONE WHO MAY BE INTERESTED IN PARTICIPATION.SCHEDULE OF PRESENTATIONS AND PANEL DISCUSSION OF 13th INTERNATIONAL WORKSHOP ON NATURAL COMPUTING (IWNC)
FRIDAY, September 17, 4:00-12:30 UTC
PLEASE CHECK FOR POSSIBLE UPDATES ON THE SUMMIT WEB PAGE
PLENARY SESSION FOR THE SUMMIT (4:00-7:00 UTC)
INVITED SPEAKERS
4:00-5:00 UTC: Genaro J. Mart´ınez – “Machines computing and learning?”
5:00-6:00 UTC: Andy Adamatzky – “Computing with slime mould, plants, liquid marbles and fungi”
6:00-7:00 UTC: Panel Discussion “Natural Question about Natural Computing”
Confirmed Panelists: Andy Adamatzky, Yukio-Pegio Gunji, Masami Hagiya, Genaro J. Mart´ınez, Yasuhiro Suzuki.
IWNC CONFERENCE SESSION (7:30-12:30 UTC)
(Only names of presenters without co-authors are displayed)
7:30 – 8:00 UTC: Yasuhiro Suzuki – “Natural Computing Systems with Tactile Sense”
8:00 – 8:30 UTC: Pedro Marijuan – “The Paradigm of Natural Intelligence”
8:30 – 9:00 UTC: Katsunobu Imai – “On sustainable self-explanatory executable document”
9:00 – 9:30 UTC: Attila Egri-Nagi – “Advancing human understanding with deep learning Go AI engines”
9:30 – 10:00 UTC: Igor Balaz – “Evolution of functionality as the emergence of logical
structures”
10:00 – 10:30 UTC: Marcin J. Schroeder – “Learning Computing from Nature: Reflection on the Klein Four-Group”
10:30 – 11:00 UTC: Kenichi Morita – “Composing reversible computers in a reversible and conservative environment”
11:00 – 11:30 UTC: Masami Hagiya – “Three Models of Gellular Automata”
11:30 – 12:00 UTC: Alan B. Cerna-Gonz´alez – “Tag Systems and their Spatial Dynamics with Cellular Automata”
12:00 – 12:30 UTC: Mark Burgin – “Validation and correction of information by computing automata”
BOOK OF ABSTRACTS
INVITED LECTURES
(TO BE DELIVERED AT PLENARY SESSION OF IWNC):
down load (PDF) --> (Click)
Friday, September 17, 2021, 5:00-6:00 UTC:
Computing with slime mould, plants, liquid marbles and fungi
Andy AdamatzkyUnconventional Computing Lab, UWE, Bristol, UK
andrew.adamatzky@uwe.ac.ukDynamics of any physical, chemical and biological process can be interpreted as a computation. The interpretation per se might be non-trivial (but doable) because one must encode data and results as states of a system and control the trajectory of a system in its state space. One can make a computing device from literally any substrate. I will demonstrate this on the examples of computing devices made from slime mould Physarum polycephalum, growing plant roots, vascular system of a plant leaf, mycelium networks of fungi and liquid marbles. The computing devices developed are based on geometrical dynamics of a slime mould’s protoplasmic network, interaction of action potential like impulses travelling along vasculates and mycelium networks, collision-based computing of plant roots’ tips and droplets of water coated by hydrophobic powder. Computer models and experimental laboratory prototypes of these computing devices are presented.
Friday, September 17, 2021, 4:00-5:00 UTC:
Machines computing and learning?
Genaro J. Mart´ınez
Artificial Life Robotics Laboratory, Escuela Superior de C´omputo, Instituto Polit´ecnico Nacional, M´exico.
Unconventional Computing Lab, University of the West of England, Bristol, United Kingdom.
genarojm@gmail.com
A recurrent subject in automata theory and computer science is an interesting problem about how machines are able to work, learn, and project complex behavior. In this talk, particularly I will discuss how some cellular automata rules are able to simulate some computable systems from different interpretations, it is the problem about universality. These systems are able to produce and handle a huge number of information massively. In this context, an original problem conceptualized by John von Neumann from the 40s years is: How primitive and unreliable organisms are able to yield reliable components? How machines could construct machines? In biological terms it refers to the problem of self- reproduction and self-replication. In our laboratories, implement these problems in physical robots, where some particular designs display computable systems assembled with modular robots and other constructions display collective complex behavior.Modular robots offer the characteristic to assemble and reconfigure every robot. In Particular, we will see in this talk a number of robots constructed by Cubelets to simulate Turing machines, Post machines, circuits, and non-trivial collective behavior. We will discuss if these machines learn and develop knowledge as a consequence of automation and information.
References
[1] Mart´ınez, G.J., Adamatzky, A., Figueroa, R.Q., Schweikardt, E., Zaitsev, D.A., Zelinka, I., & Oliva-Moreno, L.N. (2021) Computing with Modular Robots, submitted.
[2] Mart´ınez, S.J., Mendoza, I.M., Mart´ınez, G.J., & Ninagawa, S. (2019) Uni- versal One-dimensional Cellular Automata Derived from Turing Machines. International Journal Unconventional Computing, 14(2), 121-138.
[3] Mart´ınez, G.J., Adamatzky, A., Hoffmann, R., D´es´erable, D., & Zelinka, I. (2019) On Patterns and Dynamics of Rule 22 Cellular Automaton. Complex Systems, 28(2), 125-174.
[4] Figueroa, R.Q., Zamorano, D.A., Mart´ınez, G.J., & Adamatzky, A. (2019) A Turing machine constructed with Cubelets robots. Journal of Robotics, Networking and Artificial Life 5(4) 265–268.
[5] Mart´ınez, G.J. & Morita, K. (2018) Conservative Computing in a One- dimensional Cellular Automaton with Memory. Journal of Cellular Au- tomata, 13(4), 325-346.
[6] Mart´ınez, G.J., Adamatzky, A., & McIntosh, H.V. (2014) Complete char- acterization of structure of rule 54. Complex Systems, 23(3), 259-293.
[7] Mart´ınez, G.J., Seck-Tuoh-Mora, J.C., & Zenil, H. (2013) Computation and Universality: Class IV versus Class III Cellular Automata. Journal of Cellular Automata, 7(5-6), 393-430.
[8] Mart´ınez, G.J., Adamatzky, A., & Alonso-Sanz, R. (2013) Designing Com- plex Dynamics in Cellular Automata with Memory. International Journal of Bifurcation and Chaos, 23(10), 1330035-131.
[9] Mart´ınez, G.J., Adamatzky, A., Morita, K., & Margenstern, M. (2010). Computation with competing patterns in Life-like automaton. In: Game of Life Cellular Automata (pp. 547-572). Springer, London.
Moderator’s Introduction to IWNC Discussion
“Natural Question about Natural Computing”
Marcin J. SchroederThe panel discussion is scheduled on Friday,
September 17, 6:00-7:00 UTC
within the plenary session for IWNC after the two Invited Talks.
Panelists: Andy Adamatzky, Yukio-Pegio Gunji, Masami Hagiya, Genaro J. Mart´ınez, Yasuhiro Suzuki.
Introduction
The question about Natural Computing may be natural but the attempt to answer it by providing a formal definition would be pointless. Definitions of concepts serve the purpose of closing them into an existing framework of concepts with the already established intention or meaning. Natural computing is an open idea that serves the opposite purpose to transcend the currently dominating paradigm of computing. The qualifier “natural” that for centuries was a subject of philosophical disputes is used here not in the restrictive sense. After all, its common-sense negation “artificial” is associated with human skills or competencies which there is no reason to consider non-natural or at least inconsistent with human nature, human inborn capacities.
This conference is the 13th in the long series of International Workshops on Natural Computing whose participants and contributors have had diverse ways of understanding this subject. However, there was never a risk of mutual misunderstanding and there is no such risk now. What was and is common and uniting in these diverse inquiries can be expressed as the search for dynamic processes involving information that have all or some characteristics of computing, but are different from it in the form and means of implementation, procedural description, intention, outcomes, etc. The adjective “natural” reflects the interest in natural processes studied in several different disciplines of science independently from any application in computing, but it did not exclude the interests in the dynamics of information in cultural, social contexts of human life. Just opposite, Natural Computing is an attempt to bridge technological interests with natural aspects of information processing to transcend the limitations of computing, including the limitations of its present applications.
The panelists represent diverse directions of research and study within Natural Computing. I would like to ask them the question: “Quo Vadis?” (Where are you going?) Unlike in the Scriptural origin of this question, this is not a call to return to Rome. It is a request for sharing with the audience panelists’ vision of the direction and future of Natural Computing. This is a question about their motivation to pursue this path of inquiry. Finally, the panelists may choose to reflect on the more general question of the future not just of Natural Computing but Computing in general.
***
CONTRIBUTED PAPERS IN THE ALPHABETIC ORDER OF FIRST AUTHORS:Evolution of functionality as the emergence of logical structures
a) Igor Balaza, b) Koji Sawab, c) Tara Petrica
a) Laboratory of Meteorology, Biophysics and Physics, University of Novi Sad, Serbia
b) Center for Learning Support and Faculty Development,c) Doshisha University, Kyoto, Japan
Corresponding author: igor.balaz@df.uns.ac.rsDuring evolution, in order to survive, living systems gradually develop a useful approximation of their environment. During that process, organisms have to perceive environmental properties and either incorporate them into existing functional traits or create entirely novel functional combinations.
Here, we create an agent-based system where agents can evolve an internal frame of reference against which they can functionally distinguish environmental properties. Basic elements of the frame of reference are segregation (ability to distinguish environmental objects) and categorization (ability to develop a variety of functional responses to an observed environmental object). Both segregation and categorization parameters are not predefined. Instead, they are defined during the evolutionary process as a function of their contribution towards the agent’s survival. Therefore, the evolutionary development of the frame of reference is not externally guided but is driven by the internal emergence of systemic functionality. As a result, an arbitrary property of the environment becomes either (i) a proper signal that triggers a set of adaptive actions; (ii) a functionally unimportant background signal that is ignored.
In the model, the frame of reference of each agent is implemented as a growing complex network with randomly added nodes. Nodes are elementary functions (move, observe, transform …) while links between them indicate pair ordering, with an assigned probability of execution. The behaviour of agents is governed by the network structure. At each time step, the network topology can change in two fundamental ways: (i) a randomly chosen node is either added or removed to/from a random location in the network and (ii) new random links can be added to a network or existing random links can be removed. With such rewiring, we simulate the evolution of embodied cognition. The behaviour of agents on each time step is determined by traversing through their internal networks. If a node has multiple links, the order of path execution in a certain time step is determined according to the probability of execution. Each agent can develop multiple internal networks. Agents compete for limited resources and their evolution is governed by natural selection. Over time, selection strongly favours the emergence of networks that build a proper frame of reference by first identifying environmental signals and then execute a set of adaptive actions.
As a next step, we analyze logical structures that appear and grow during the evolution by transforming growing random complex networks into graphs that represent formal logic. An arbitrary directed graph does not necessarily hold all the properties of formal logic. Therefore, we first determine necessary axioms (e.g. axiom of pairing, the composition of logical connectives, the emergence of transitive law). Then, we analyze temporal (composition of functions by ordered pairs) and spatial (representation by non-ordered pairs) logical properties. We finally discuss the parallel generation of functionality and logical structures with spatial and temporal aspects.Validation and correction of information by computing automata
Mark Burgin and Karthik Rajagopalan
UCLA, Los Angeles, California, USA
markburg@cs.ucla.eduLearning is an important category of information acquisition. Machine learning utilizes automata for learning in general and language learning in particular. In addition, abstract automata are used for modeling learning by people. In this work, analyzing how people learn natural languages, we develop a new approach to modeling and performing language learning by abstract automata. This allows treating natural language learning as natural computing.
The conventional models of natural language acquisition assumes that in the process of learning, children, as well as adult learners, find out and memorize the correct words, rules of generating sentences, and rules of their utilization. However, this picture misses an important peculiarity of the learning process. Namely, people also gain knowledge of incorrect words and sentences and this knowledge helps not to use incorrect linguistic constructions in communication.
To model this process, we introduce a new type of computational automata called selective machines. A selective machine can not only generate (compute) words and texts but also eliminate (uncompute) words and texts. This property allows achieving higher power and lower complexity in computations.
A selective machine M has positive and negative processors which accept/recognize words.
The difference between positive and negative processors is their purpose of computation. Positive processors accept or recognize tentative (or possible) elements of a language. However, it is not assumed that all of them are correct (belong to the language under construction). The goal of negative processors is to recognize those elements that do not belong to the language under construction, that is, are incorrect. This allows building a language by the procedure where at first, tentative (or possible) elements of the language are extracted and then the incorrect words are eliminated.
We remind that a language L is accepted or recognized by a conventional automaton (machine) M, such as a finite automaton or a Turing machine, if this automaton accepts all words from L and only these words. It is denoted by LM or L(M) and is also called that language of the machine M.
In the case of selective machines, we have two types of languages.
The positive language L(MP) of a selective machines M is the language accepted/recognized by all positive processors of M.
The negative language is defined in a similar way.
The negative language L(MN) of a selective machines M is the language rejected/eliminated/prohibited by any of the negative processors of M.
Positive and negative languages together recognize the language of selective machines in the following way.
The language L(M) = L(MP) \ L(MN) is the language of the selective machine M.
Taking two classes K and H of automata (algorithms), we denote by K/H the class of all selective machines, in which the positive processors are automata from K and the negative processors are automata from H.
We remind that the recognizing linguistic power RL(A) ( RL(Q) ) of an automaton A (a class Q of automata) is the class of all formal languages recognized by the automaton A (by the automata from the class Q).
The goal of this work is to study the recognizing linguistic power of different classes of selective machines, for example, such as FA/TM or TM/TM, and compare their powers with the recognizing linguistic power of different classes of the basic classes of conventional recognizing automata, such as the class FA of all finite automata with a given alphabet, class TM of all Turing machines or class ITM of all inductive Turing machines.
It is possible to ask the question why the same automaton cannot generate words and exclude those that do not belong to the language under construction. The answer is yes it is possible but the results proved by the authors demonstrate that in many important cases, two automata – one positive and another negative, which belong to the same class K (for example, both are Turing machines) can generate, describe and recognize much more languages than one automaton from this class K (one Turing machine) can do.
To conclude, it is necessary to remark that before this approach to learning was studied in the context of formal grammars (Burgin, 2005; Carlucci, et al, 2009; Case and Jain, 2011). Here we explore learning as a natural information acquisition process modeling it with computing automata.
References
1. Burgin, M. Grammars with Prohibition and Human-Computer Interaction, in “Proceedings of the Business and Industry Simulation Symposium,” Society for Modeling and Simulation International, San Diego, California, 2005, pp. 143-147
2. Carlucci, L., Case, J. and Jain, S. Learning correction grammars. J. Symb. Logic, 74, 2009, 489-516
3. Case, J. and Jain, S. Rice and Rice-Shapiro theorems for transfinite correction grammars, Math. Logic Quarterly, 57(5), 504-516 (2011)
Tag Systems and their Spatial Dynamics with Cellular Automata
Alan B. Cerna-Gonz´alez 1, Genaro J. Mart´ınez1,2,3 Andrew Adamatzky 2, Guanrong Chen 3
1 Artificial Life Robotics Laboratory, Escuela Superior de C´omputo, Instituto Polit´ecnico Nacional, M´exico.
2 Unconventional Computing Lab, University of the West of England,
Bristol, United Kingdom.
3 Centre for Chaos and Complex Networks, City University of Hong Kong, Hong Kong, China
email: acernag1500@alumno.ipn.mxIn 1920, Emil L. Post had developed a string rewriting logistic computational model that is a simple form of the normal canonical Post machine, this machine receives a string read the first symbol, deletes a constant number (defined by a deletion number P ) of symbols at the be- ginning and appends, according to the symbol found at the beginning of the string, a string of symbols at the end (called production rule), this happens until there is not a sufficient number of symbols to delete or it is reached by halt symbol. Tag systems has applications on pure mathematics, logic, computation and, in recent proposals, physics. Cellular automata have been used for discrete modelling of dynamic and complex systems, their parallel computing capacity and the simplicity that make them as a functional and efficient tool. Also, cellular automata are able to express formal language into their evolution space. Both tag systems and cellular automata have been used to simulate universal Turing machines. This way, we research the production of strings from a tag system as a dynamical system evolution and show some particular cellular automata rules simulating specifically some tag systems. We discuss about how cellular automata can be used as a tool in tag systems evolution, by using the rules that we found and some tag systems. We also discuss the theory and computational model of parallel evolution of a tag system based on cellular automata. The basic idea of this analysis is based on the action of dynamics, which is relevant to the conceptualisation of the evolution of the overall system. A cellular automaton can be characterised by its evolution. The characterisation of the entire system depends on its behaviour. So, the tag systems that we simulated can be characterised on the spatial behaviour of the equivalent cellular automata.
Advancing human understanding with deep learning Go AI engines
Attila Egri-Nagy & Antti Törmänen
Akita International University, Akita Japan
egri-nagy@aiu.ac.jp
Improvement is a central issue for all serious players of pure skill board games. Which book to read? Which master to listen to? How to practice? Questions like this are often asked in the process of getting better. For Go players, the appearance of deep learning AI engines suddenly opened up new learning possibilities as they encode superhuman level playing skills, albeit in a black-box format. How can we improve our understanding of the game of Go by using the deep learning neural network AI engines? The research focus is shifting from creating more powerful AIs to enabling human players at all levels to benefit the technological advances. We start from the fact that the human mind has a better cognitive architecture. We have explanations, reasoning, the ability to form hypotheses and test them. In contrast, the AIs (AlphaGo and subsequent open-source implementations) are purely associative structures, mapping board positions to estimated results and good moves. From this perspective, it is somewhat ironic that a narrow AI advanced beyond the only AGI currently in existence, the human intelligence.
Arguably, this happened several times before, but this situation is more interesting than the case of the calculator (with superhuman calculating skills) since we do not do arithmetic by intuition.
There are two different approaches for using AIs as tools for learning about the game. We can try to open the black box of the neural network or embrace its opaque nature.
1. Internal analysis of the neural networks - intelligible intelligence: Unlike in the brain, we have complete access to the whole neural network, down to single neurons. We can try to uncover the abstract hierarchical representation of Go knowledge inside the network by using feature visualization. However, we know that neural networks may or may not have comprehensible representations. The space of possible Go-playing neural networks may have a vanishingly small fraction in human accessible formats.
2. Improve our learning methods: Learning at a professional level proceeds from intuitive understanding to explicit verbalizations. In the case of Go, strategic plans are explanations for what is happening on the board. Therefore, the methods of scientific knowledge creation do apply here. The AIs are inexhaustible sources of experiments providing high-quality statistical data. Growing Go knowledge can be faster by formulating plans when choosing moves rather than just looking up the best move recommended by the AIs.
We focus on the second case and we will review the existing practices of working with AIs in the Go community and study how a more deliberate application of scientific principles can enhance the human learning process.
Three Models of Gellular Automata
Masami Hagiya
University of Tokyo
hagiya@is.s.u-tokyo.ac.jpWe summarize our work on gellular automata, which are cellular automata we intend to implement with gel materials. If cellular automata are implemented as materials, it will become possible to realize smart materials having abilities such as self-organization, pattern formation, and self-repair. Furthermore, it may be possible to make a material that can learn from its environment. In this talk, we present three models of gellular automata, among which the third one is new.
Suppose such a smart material implements an artificial blood vessel. In that case, the vessel will be autonomously formed at an appropriate place in the living body, and it will recognize its deformation or occlusion and self-repair. Furthermore, it is possible to envision smart materials that learn appropriate functions by external stimuli.
The first model of gellular automata is based on gel walls separating cells of solutions. The gel walls are assumed to have holes that open and close by the surrounding solutions. We showed the Turing computability of the model by encoding rotary elements in the model.
The second model is much simpler than the first one and more suitable for implementation with gels. Gel walls also separate cells of solutions, but communication between cells is realized by diffusion of signal molecules as actually implemented by Murata and his colleagues. In addition to the Turing computability, we focus on self-stability in relation to the ability of self-repair.
We finally report our recent attempt in the third model to design gellular automata that learn Boolean circuits from input-output examples. In the model, supervised learning is realized as a kind of pattern formation. If smart materials gain such an ability, they can learn from their external environment. A cell is placed at each lattice point of a three-dimensional space. Each cell has therefore six neighbors. Some cells are specified as input nodes or output nodes. Other cells are either active or inactive. If a cell is active, it works as an OR gate. Boolean circuits are constructed in the three-dimensional cellular space. With Boolean values at input nodes, expected Boolean values at output nodes are specified as teacher signals. In other words, an example for supervised learning consists of given values at input nodes and expected values at output nodes. With each example, cells make state transitions and form a Boolean circuit consisting of OR gates between input and output nodes.On sustainable self-explanatory executable document
Katsunobu IMAI
Hiroshima University
imai@hiroshima-u.ac.jpIn recent years, we have been looking for a framework that can support our daily personal tasks, even in the presence of cognitive decline or fluctuations due to dementia or higher brain dysfunction. Our documents are usually not just static, but including executable documents with associated scripts. In order to ensure their readability as well as executability, careful choice of its supporting programming language and how to keep daily records are important issues.
The condition for an "ideal" sustainable self-explanatory executable document is:
1. I can understand and execute the documentation.
2. If 1 is impossible, \[Exists] x, I can show the document to others and ask x to help me understand and execute it.
3. If 1 and 2 are impossible, \[ForAll] x, x can understand and execute the document independently of me.
These are very important settings. We have to assume that we will not only have forgotten the documents we wrote, but not be able to process them in future. However it seems quite difficult to achieve because:
1. If your age is x years old, you need to expect the documents to be executed after 90-x years.
2. Your cognitive level will not remain the same for the period of time.
Over the past 50 years, many file formats for executable documents have been proposed, but most of them have been lost and only a few remain readable and executable to this day. This problem becomes more difficult because of the complexity of privacy issues related to personal documents.
In this study, we discuss the historical background and potential applications of self-explanatory executable documents. Our goal seems hopelessly difficult to achieve, but we need to present the best possible solution. However, since a general discussion is impossible, I will only describe my personal measures to achieve this goal.The Paradigm of Natural Intelligence
Pedro C. MarijuánIndependent Scholar, affiliated to Aragon Institute of Health Science (IACS, Bioinformation Group), Zaragoza, 50009, Spain pcmarijuan.iacs@aragon.es
It will be argued that intelligence is a universal phenomenon present in all forms of life. It requires a new form of relationship with the environment, implying not only openness to energy flows but to information flows as well. External information processing, coupled with internal information processing, may produce an adaptive life cycle that manifests (‘natural’) intelligence, produces meaning, and realizes fitness value. Out from the basic prokaryotic conformation, the fundamental unit of natural intelligence, this phenomenon will develop hierarchically, via multicellularity, and particularly with the evolution of animal nervous systems. Then, natural intelligence will fully develop up to the point, in the human case, of exhibiting pieces of artificial intelligence that mimic some of the basic properties of the former—but they should not be confused. In contemporary societies, the essential link between intelligence and life has to be plainly revealed as a counterpoint to the link between artificial intelligence and computation.1. THE CELL AS THE BASIC UNIT OF INTELLIGENCE
It is argued that without a proper understanding of natural intelligence, the scientific foundations of artificial intelligence will be shaky--notwithstanding the technological grandeur it is effectively achieving. Information processing is at the heart of natural or biological intelligence, but it is very different from the way it is organized in artificial systems (Marijuán et al., 2015; Slijpevic, 2018). The living cell provides an alternative paradigm, a new conceptual panorama, where information flows, signaling systems, gene transcription and protein synthesis are contemplated as a coherent unit. It is the adaptive life cycle, which can manifest intelligence, can communicate and produce meaning, and finally is capable of evolving. In an artificial system we would be talking about perception, memory, learning, anticipation, decision-making, etc., all of them carried by means of computations. But the ‘mechanics’ of natural intelligence is utterly different.
2. THE PROKARIOTIC LIFE CYCLE
We see the life cycle of cellular sytems (the simplest ones, prokaryotes) as a trivial characteristic of life, but actually it is the most amazing information design any engineer could think of. The living cell is a system that self-constructs out from environmental stuff according to an inner blueprint that is separated from the constructive system itself (echoing von Neumann self-reproducing automata). In the distributed constructing system of multiple ribosome nanomachines we find a complex conjunction of informational architectures supported by inner ‘computational protein networks’ capable of sending their signals across distant functional areas. This vast constructive process distributed across the cell system only needs some transient copies of mRNAs and the raw basic materials. Reproduction will follow. With unencumbered repetition of the reproduction cycles, there is a tendency to excess, to fill in the ecological niche; but the emerging trophic interactions will put all participants “in their place.” Further, systemic variations affecting the blueprint will appear, becoming phenotype changes and implying differential survival; thus evolution occurs… and quite many evolutionary ‘vehicles’ will be assembled in multicellular organisms for the adaptive exploration of the new complexity scenarios, implying both DNA blueprint and interactive behavior in the coupled environment (Wagner, 2019).
3. FROM EUKARYOTIC CELLS TO MULTICELLULAR ORGANISMS
The different kind of intelligence that eukaryotic cells evolve with respect to prokaryotic cells has been discussed thoroughly in (Marijuán et al., 2010, 2013). In some sense, the further complexity growth we see in multicellular organisms is a déjà vu of the prokaryotic phenomenology. In another sense, the uncanny complexity of signaling and transcriptional processes in all the eukaryotic kingdoms of life challenges the meaningfulness of whatever simplified scheme we may propose. Nevertheless, there are a few evolutionary guidelines on the fundamentals of the ‘new eukaryotic order’: symbiosis, signaling expansion, cell-cycle modularity, and ontogenetic multicellular development.
The further evolution of intelligence in Nature has kept pace with the progressive complexification and sophistication of the nested information flows that subtend and involve all the different realms of life (Wurtz, 2021). From the signaling pathways of unicellular prokaryotes to the signaling systems of multicellular eukaryotes, and to the central nervous systems of vertebrates, advanced mammals and anthropoids—organized not only in ecosystem networks but also in close-knit societies. This evolutionary capability to arrange complex organisms and complex organizations behaving sophisticatedly in an open-ended environment has represented the definite emergence of the phenomenon of intelligence in Nature and at the social level.4. FROM HUMAN INTELLIGENCE TO SOCIAL INTELLIGENCE
Seemingly the linguistic capability of humans has put our societies in an entirely new path. That’s right, but we can also analyze the evolution of the information flows and the processing structures in our societies along some of the previous guidelines: both the natural information flows related to the individual lives and the artificial flows generated via technological systems. Like in the case of cells or in nervous systems, a degree of “social intelligence” might also be ascertained regarding the combined working of social entities and institutions.
In human societies, the new thinking derived from natural intelligence and information science should contribute to a more cogent social management of the whole system of sciences. The art of “knowledge recombination” has to be practiced with some more scientific guidance, so that the immense body of scientific knowledge accumulated –in the order of 6,000 disciplines– becomes useful to reorient the productive system and to grant collective sustainability. A new scientific culture has to be promoted; a new dialog among theoretical and experimental scientists and philosophers from very different fields has to be established; and the natural phenomenology underlying the essential link between intelligence and life has to be plainly revealed as a counterpoint to the link between artificial intelligence and computation. In the extent to which this can be achieved, an important social mission will be fulfilled.
References
Marijuán, P.C., Navarro, J., del Moral, R. 2010. On prokaryotic intelligence: strategies for sensing the environment. BioSystems 99, pp: 94-103.
Marijuán, P.C., del Moral, R., Navarro, J. 2013. On eukaryotic intelligence: signaling system’s guidance in the evolution of multicellular organization. BioSystems 114, pp: 8-24.
Marijuán, P.C., Navarro, J., del Moral, R., 2015. How the living is in the world: An inquiry into the informational choreographies of life. Progress in Biophysics and Molecular Biology. 119 (3): 469–480.
Slijepcevic, P. 2017. Evolutionary Epistemology: Reviewing and Reviving with New Data the Research Programme for Distributed Biological Intelligence. Biosystems. 163. 10.1016/j.biosystems.2017.11.008.
Wagner, A. 2019. Life Finds a Way: What Evolution Teaches Us about Creativity, Oneworld Publication.
Wurtz, T. 2021. Nested information processing in the living world. Ann. N.Y. Acad. Sci.. https://doi.org/10.1111/nyas.14612Composing reversible computers in a reversible and conservative environment
Kenichi Morita
Hiroshima University
(Currently Professor Emeritus of Hiroshima University)
km@hiroshima-u.ac.jp
Reversibility is one of the fundamental physical laws of nature. We study the problem of how we can construct reversible Turing machines (RTMs) in an environment that obeys a reversible and conservative microscopic law. Here, we use the framework of an elementary triangular partitioned cellular automaton (ETPCA) as a spatiotemporal model of the environment. In an ETPCA, configurations evolve according to an extremely simple local transition function, and hence it is suited for investigating how simple computationally universal reversible CAs can be.
Thus, the problem is to find an effective construction pathway that starts from a local transition function of an ETPCA, and leads to RTMs.
In our previous research, it was shown that RTMs can be constructed systematically in a reversible and non-conservative ETPCA 0347, where 0347 is an ID number in the class of 256 ETPCAs [2,3].
Here, we solve this problem in a reversible and conservative ETPCA 0157. In [1], a Fredkin gate, which is a universal reversible logic gate, can be realized in the cellular space of ETPCA 0157. Hence, RTMs are, in principle, realizable in this cellular space. However, if we use reversible logic gates the resulting circuit becomes very complex, since two or more signals must arrive at exactly the same time at each gate. Here, we use a reversible logic element with memory (RLEM), rather than a reversible gate, as a logical primitive. By this, the whole circuit is greatly simplified.
Here, several conceptual levels are appropriately introduced on the construction pathway, and hence the problem is decomposed into several sub-problems. These sub-problems are the following:
(1) Finding useful patterns and phenomena in ETPCA 0157,
(2) making an RLEM by utilizing these phenomena,
(3) composing functional modules for RTMs out of RLEMs, and
(4) constructing RTMs by assembling these functional modules.
By these steps, RTMs are constructed systematically and hierarchically even from
a very simple local transition function.
References
[1] Imai, K., Morita, K.: A computation-universal two-dimensional 8-state triangular reversible cellular automaton. Theoret. Comput. Sci., Vol. 231, pp. 181-191 (2000). DOI: 10.1016/S0304-3975(99)00099-7
[2] Morita, K.: A simple reversible cellular automaton that shows complex behavior. 11th Int. Workshop on Natural Computing (IWNC), Akita, 2017.
[3] Morita, K.: Finding a pathway from reversible microscopic laws to reversible computers.
Int. J. Unconventional Computing, Vol. 13, pp. 203-213, 2017.Learning Computing from Nature:
Reflection on the Klein Four-Group
Marcin J. Schroeder
IEHE, Tohoku University, Sendai, Japan
mjs@gl.aiu.ac.jp
Qualification of computing as natural can be interpreted in many essentially different ways. It will be understood here as the functioning of models of the information transformation acquired through abstraction from similar processes in natural phenomena occurring without any engagement of the human purpose oriented action. In a slightly oversimplified form, natural computing is one which is discovered while artificial is invented. Turing Machine could qualify as natural computing device (human computers observed by Turing did not have any idea about the purpose of their work), but its special version of the Universal Turing Machine as artificial (it was not derived from an observation of a natural process and it was designed with the specific purpose of the simulation of all other Turing Machines). Another example of natural computing can be identified in the Artificial Neural Networks derived from the observation of natural neural systems. Certainly, better name would have been Abstract Neural Networks, but this is not our concern.
The subject of this study is the quest for new and essentially different forms of natural computing. The central question is about the promising directions for exploration of natural phenomena in which new paradigms of computing could be found. An example of success in designing innovative computing can be the model of quantum computing. However, someone can question how much conceptually innovative it is (quantum phenomena where involved in the technological progress of computing devices from the very beginning) and quantum computing clearly belongs to what here is understood as artificial computing (result of the attempts to overcome the limits of speed in standard computing).
The most likely domain of natural phenomena involving really innovative forms of information processing is life with its extremely high level of complexity and efficiency. The main assumption of this study is that the two aspects of natural information processing deserve closer inspection: the capacity of information integration and the complex hierarchic architecture of information processing reflecting the complexity of the organization of life.
The interest in both these aspects is not entirely new. Integration of information became one of key concepts in the search for scientific explanation of phenomenal consciousness. Hierarchic architecture of neural networks is the basis for deep learning. However, in both cases there is no fundamental theoretical formulation of the idea of integration or hierarchy. Integration is identified with statistical patterns of observed simultaneous activations of neurons in terms of mutual entropy, while layers of neurons in the network with directional convergence of connections are the only hierarchic configuration considered. There is no description of the mechanism of integration or analysis of the influence of the possible alternative forms of hierarchies.
I provided in my earlier publications mathematical model of information integration (including the description of integrating gates) and of the hierarchic architecture of computing. The former is based on the conclusions from the algebraic characterization of the degree in which a system is classical or quantum type (degree of the product irreducibility of its underlying logic). Here, I will focus on only one aspect of hierarchic organization of computing: the transition between different levels of structural complexity. The study can be summarized as an attempt to answer the question: What is the role of the humble Klein Four-Group?
Natural Computing Systems with Tactile SenseYasuhiro Suzuki
Graduate School of Informatics, Nagoya University
ysuzuki@nagoya-u.jpWe construct a natural computing system based on the sense of touch. The natural computing system we construct does not depend on the conventional category of computer science. The computing consists of a computing entity and an algorithm. We define an algorithm as "a list of instructions for solving a problem" and a computing system as "the act or process of calculating an answer or amount by using an algorithm".
Interactions can be divided into two types: the actor and the target of the action are clear or not. For example, in the interaction by e-mail, the actor and the target are clear. On the other hand, in daily conversation, non-verbal interactions such as facial expressions and behaviours are added to verbal interactions. Therefore, the actor and the object of action cannot be separated. The change in the other person caused by one's speech changes one's speech and facial expressions. In other words, by acting on the other person, we receive an action from the other person.
We define this kind of ambivalent action as tactile interaction. The sense of touch is ambivalent; we can block the action of sight by closing our eyes, while we cannot close our sense of touch as we close our eyes.
Tactile interactions are common in nature. For example, molecular and cellular interactions are tactile interactions; when a vaccine is administered to the immune system, the immune system remembers the molecules to attack. However, neither the immune system nor the target molecule is auditory. Molecular recognitions rely on tactile of the shape of molecules. In viruses, macromolecules called glycans act as molecular "tags", and proteins and glycans "touch" the cell surface to search for the most stable contact position.
We define a tactile computing system as a system in which an algorithm designs the interaction. For example, the system of the immune system and viruses is a tactile computing system. The way the sugar molecules are arranged, i.e. the algorithm, mediates the interaction. The virus changes the arrangement of sugar molecules to escape the immune system's attack and becomes a so-called mutant. We define programming as the modification of the algorithm according to the purpose.
We have proposed Tactile Score, TS, a notation that describes the Spatio-temporal pattern of tactile interaction. In TS, a staff notation with the third line representing the average interaction force, the lower line representing the strong interaction force, and the upper line representing the weak interaction force. The duration of the interaction force is described using musical notes. For example, if a quarter note is one second, an interaction force of a certain magnitude lasting for two seconds is described by a half note.
We have been using the Tactile score to convert various natural systems into computing systems. Recently, we have been applying tactile computing systems to the treatment of dementia. There are very few effective treatments for dementia, such as Alzheimer's disease and Parkinson's disease, and the primary treatment is medical-drug therapy. We are conducting clinical research on haptic interaction to treat dementia. We have used direct tactile stimulations and indirect tactile stimulations by ultra-low frequency (Deep Micro Vibrotactile, DMV, we invented) in clinical research with Advanced Research Center for Geriatric and Gerontology, Akita University (prof. Hidetaka Ota) [2]. A preliminary clinical study showed that both methods improved cognitive function; these clinical studies indicate that this method is also effective for depression and insomnia. We are currently searching for more effective algorithms. Our tactile computing system has been successfully applied not only to dementia but also to medical treatment of the elderly (prevention of frailty) and beauty care.
Natural computing with tactile sense has only just begun. We have accumulated much knowledge in computer science, molecular computing and molecular robotics. We aim to develop research on natural tactile computing systems by making the best use of them.Acknowledgement:
This research has supported by Grant in Aid for Scientific Research, 21K12108
References
[1] Yasuhiro Suzuki and Rieko Suzuki, Tactile Score, A Knowledge Media for Tactile Sense, Springer Verlag, 2014.
[2] Kodama A, Suzuki Y, Kume Y, Ota H (2021) Examination of the effect of Deep Micro Vibrotactile stimulation on cognitive function for elderly with Alzheimer’s Disease. Ann Alzheimers Dement Care 5(1): 001-003. DOI: 10.17352/aadc.000016.International Workshop on Natural Computing
SIG-NAC has been organized International Workshop on Natural Computing, since 2006; Postceedings of workshop have been published from Springer Verlag
- Past Workshops
1st, Dec 14-15, 2006 : University of West-England, Bristol, UK
2nd, Dec 10-13, 2007 : Nagoya University, Nagoya, Japan
3rd, Sept. 23, 2008 : Yokohama National University, Yokohama, Japan
4th, Spet, 23-19, 2009 ; Himeji International Exchange Center, Japan
5th, Sept, 21, 2010 ; Ascoli Piceno, in ACRI2010, Italy
Mar, 15-16, 2011; as "Winer School of Hakodate", Future University Hakodate, Japan
6th, Mar, 28-30, 2012; Tokyo University, Tokyo, Japan
7th, Mar, 20-22, 2013; Tokyo University, Tokyo, Japan
8th, Mar, 18-19, 2014; YMCA, Hiroshima, Hiroshima, Japan9th, Mar. 15, 2015; Tokyo University, Tokyo, Japan
- International Workshop
7 Oct, 2013, National Taiwan Normal University, "Taiwan-Japan workshop on Computational Aesthetics"
27 Oct, 2013, Keio University, JAPAN, Natural Computing meets Computational Aesthetics
- Open Access Volume (free to read)
Winter School of Hakodate + IWNC6th
9th International Workshop on Natural Computing
13, March 2015
Ito International Research Center, University of Tokyo, JAPAN
Co-Organized by: Grant-for-Aid in Scientific Research for Innovative Area "Molecular Robotics", Ministry of Education, Culture, Sports, Science and Technology, JAPAN
International Workshop on Natural Computing: Workshop for all related areas of Natural Computing, we never LIMIT the scope, but expand research field broadly; of course we all welcome "so-called" natural computing researches but also we have been including (fine / media / modern) art, aesthetics, design, sociology so if you feel your research is not ordinary and hard to find out meetings to join... you are the right person to join this workshop ;-)
-PROGRAM
9th International Workshop on Natural Computing
13. Mar. 2015
Ito International Research Center, the University of Tokyo, JAPAN
Organized by SIG-NAC, the Japanese Society for Artificial Intelligence
Co-Organized by: Grant-for-Aid in Scientific Research for Innovative Area
"Molecular Robotics", Ministry of Education, Culture, Sports, Science and
Technology, JAPAN
Program; (20min presentation + 10 min discussion)
BUT we do not have to rush, so take it easy..
10:00-10:30 Yasuhiro Suzuki
Computational Model of Proto-cells and its behaviors
10:30-11:00 Ayano Yoshida
11:00-11:30 Shigeru Sakurazawa
Effects of physiological tremor on haptic perception
11:30-12:00 Miki Goan
Drawing mediated by medium perception robots
Lunch Break (12:00-13:30 incl. buffer 30min.)
13:30-14:00 Katunobu Imai
14:00-14:30 Hiroshi Umeo
A Class of Non-Optimum-Time FSSP Algorithms for One-Dimensional Arrays - A Survey
14:30-15:00 Teturo Itami, Nobuyuki Matsui (University of Hyogo)
Experimental Study on "Macroscopic" Brownian Motion using Sphere shaped robots
Break around 30 min (buffer + 30min)
16:00-16:30 Marcin J. Schroeder
Naturalization of Computation through Naturalization of Information Dynamics Which Defines Computation
16:30-17:00 Fuminori Akiba
(about 18:00 Yasuhiro Suzuki (buffer.. depend of schedule)
Natural Computing for Sensory Communication)
17:20-17:30 Business meeting
17:30 Closing
19- Banquet
-----
*Abstracts
Effects of physiological tremor on haptic perception
Shigeru Sakurazawa
Future University Hakodate
Abstract
Human fingers always continue to vibrate at around 10 Hz even though there are no pathological factor. This phenomenon is called as physiological tremor. It changes depending on the objects which the human is willing to touch. From this situation, there is a possibility that physiological tremor has some function for haptic perception. To research effects of physiological tremor on haptic perception, we tried to test human finger’s discrimination ability of hardness under the condition that the tip of a finger is vibrated by an oscillator at 10Hz. The results showed that the vibration enhanced the discrimination ability of hardness. It is thought that haptic perception is a kind of orientation as the echolocation which is brought by searching with periodical dynamic action to the environment.----
Effect of a state and locomotion change by chemical reaction on macro pattern formation
Ayano Yoshida
Future University Hakodate
There are some phenomena in which the macroscopic structure is emerged with mixing the two
solutions which has different characteristic or concentration. One of them is forming a microcapsule
of thermal heterocomplex molecules of amino acids. It is considered that this microcapsule is made
by raising solution pH resulting from dissolution of microsphere. Here, it is thought that not only
state changes of molecules but also their diffusional motions associated with their chemical reaction
in microscopic area is important for these macroscopic structure emergence. In this study, the system
including the change of the diffusional motion by molecule’s state change resulting from their
chemical reaction was used. Then, by comparing the materials which change their diffusion
coefficient by their chemical reaction with the materials which do not change one, we researched
that how the diffusional motions change resulting from state change in microscopic effect to
macroscopic structure emergence.10th International Workshop on Natural Computing, IWNC 10
14-15 May, Akita International University
cooperated by Molecular Robotics: Grant in Aid for Scientific Research
SIGNAC, Japan Society of Artificial Intelligence
about the workshop
The series of International Workshops on Natural Computing initiated in 2006 grew up from the original interest in molecular computing. However, within the years following this original initiative the topic of natural computing became one of main directions of study in several disciplines. Natural processes or even entire life started to be considered a form of information processing with characteristics of computing. On the other hand, information processing in natural systems became a source of inspiration for innovation in computer science, artificial intelligence and engineering. Moreover, computer simulation became a common tool for study of nature. Following this general trend of mutual interactions of disciplines the 10th International Workshop on Natural Computing is devoted to the recent and future developments in research, practice, philosophical reflection and creative activity within the crossroads of nature, computing, information science, cognitive science, study of life and culture.
The intention of the workshop is to bring together a very wide range of perspectives from philosophical to scientific ones, to visions of artists. There will be an opportunity to present original and creative contributions without any restriction by disciplinary divisions or the level of advancement of research. Contributions from the beginning of the academic or intellectual career are as welcome as those from its peak.
REGISTRATION:
Participants do not have to pay registration fee, but they have to cover from own funds the cost of travel, accommodation, and of the optional social event (dinner). Registration for the workshop is necessary for the purpose of planning and logistics.
ORGANIZING COMMITTEE:
Masami Hagiya (Tokyo University) hagiya@is.s.u-tokyo.ac.jp
Yasuhiro Suzuki (Nagoya University) ysuzuki@nagoya-u.jp
Marcin J. Schroeder (Akita International University) mjs@aiu.ac.jp
CALL FOR Abstracts
CALL FOR CONTRIBUTIONS:
We invite submission of abstracts for intended presentations at the workshop. Abstracts should be in English and they should be sufficiently extensive to describe clearly the content of presented work, but their expected volume is within 200-500 words. The subject matter of presentations is not restricted to specific disciplines or topics, but the originality of the presented work and relevance to the main theme of the workshop is expected.
Contributed presentations are planned for 30 minutes including 20-25 minute lecture and 5-10 minute discussion.
DEADLINE for submissions: May 6, 2016. Acceptance notices will be sent within one week of submission, but not later than May 9, 2016. Late submissions may be considered, but in order to secure full consideration, please meet the deadline. Submissions can be sent any time after this announcement to ysuzuki@nagoya-u.jp or mjs@aiu.ac.jp
Submissions should include together with the abstract (information required at the time of submission is marked with the asterisks):
- Title of the presentation*
- Names of the authors with an indication who will present*
- Affiliations of the authors and their e-mail addresses*
- E-mail address of the contact person*
- Information regarding intended participation:
- - How many participants?
- - Which days? Two days, first, second?
- - Do you need reservation for accommodation in Akita? For how many people? How many hotel rooms? (info about accommodation is included below)
- - Do you want to participate in the evening social event on Saturday (dinner)? How many people of your party would participate in the dinner?
Invited Speaker: dr. Peper Ferdinand
Center for Information and Neural Networks,National Institute of Information and Communication Technology, JAPAN
Accommodation
Participants in the workshop may stay in Krypton Hotel (Official Guest Accommodation for AIU at the border of AIU campus) for discounted price of 7,000 yen per night. However, to secure availability of accommodation at Krypton Hotel please consider making arrangements for reservation as early as possible by contacting us with your request. You can make request at the time of submission of your abstract.
Past IWNC
PAST WORKSHOPS IN THE IWNC SERIES:
1st, Dec 14-15, 2006 : University of West-England, Bristol, UK
2nd, Dec 10-13, 2007 : Nagoya University, Nagoya, Japan
3rd, Sept. 23, 2008 : Yokohama National University, Yokohama, Japan
4th, Spet, 23-19, 2009 ; Himeji International Exchange Center, Japan
5th, Sept, 21, 2010 ; Ascoli Piceno, in ACRI2010, Italy
Mar, 15-16, 2011; as "Winer School of Hakodate", Future University Hakodate, Japan
6th, Mar, 28-30, 2012; Tokyo University, Tokyo, Japan
7th, Mar, 20-22, 2013; Tokyo University, Tokyo, Japan
8th, Mar, 18-19, 2014; YMCA, Hiroshima, Hiroshima, Japan9th, Mar. 15, 2015; Tokyo University, Tokyo, Japan
11th International Workshop on Natural Computing
13 (Sat.)-14(Sun) May, 2017
Akita International University Akita JAPAN
SIGNAC, Japan Society of Artificial Intelligence
about the workshop
The series of International Workshops on Natural Computing initiated in 2006 grew up from the original interest in molecular computing. However, within the years following this original initiative the topic of natural computing became one of main directions of study in several disciplines. Natural processes or even entire life started to be considered a form of information processing with characteristics of computing. On the other hand, information processing in natural systems became a source of inspiration for innovation in computer science, artificial intelligence and engineering. Moreover, computer simulation became a common tool for study of nature.
Following this general trend of mutual interactions of disciplines the 11th International Workshop on Natural Computing continues already established tradition of the IWNC series to devote its sessions to the recent and future developments in research, practice, philosophical reflection and creative activity within the crossroads of nature, computing, information science, cognitive science, study of life and culture.
The intention of the workshop is to bring together a very wide range of perspectives from philosophical to scientific ones, to visions of artists. There will be an opportunity to present original and creative contributions without any restriction by disciplinary divisions or the level of advancement of research. Contributions from the beginning of the academic or intellectual career are as welcome as those from its peak.
REGISTRATION:
Participants do not have to pay registration fee, but they have to cover from own funds the cost of travel, accommodation, and of the optional social event (dinner). Registration for the workshop is necessary for the purpose of planning and logistics.
CALL FOR CONTRIBUTIONS (ABSTRACT):
We invite submission of abstracts for intended presentations at the workshop. Abstracts should be in English and they should be sufficiently extensive to describe clearly the content of presented work, but their expected volume is within 200-500 words. The subject matter of presentations is not restricted to specific disciplines or topics, but the originality of the presented work and relevance to the main theme of the workshop is expected.
Contributed presentations are planned for 30 minutes including 20-25 minute lecture and 5-10 minute discussion.
PROGRAM:
Poster (pre workshop lectures, 12.May):
Transportation (BUS time table) :
JR Wada station <-> AIU
https://uploads.strikinglycdn.com/files/21b8884a-0e3f-45d8-abf5-3a1682f2d19b/WadaLine.pdf?id=71337
Aeon <-> AIU
https://uploads.strikinglycdn.com/files/21b8884a-0e3f-45d8-abf5-3a1682f2d19b/AeonLine.pdf?id=71338
IMPORTANT DATE:
April 23, 2017. Acceptance notices will be sent within one week of submission. Late submissions may be considered, but in order to secure full consideration, please meet the deadline. Submissions can be sent any time after this announcement to ysuzuki@nagoya-u.jp and/or mjs@aiu.ac.jp (we recommend sending your submissions to both addresses to ensure faster processing).
ACCOMMODATION:
Participants in the workshop may stay in Krypton Hotel (Official Guest Accommodation for AIU at the border of AIU campus) for discounted price of ca. 7,000 yen per night. However, to secure availability of accommodation at Krypton Hotel please consider making arrangements for reservation as early as possible by contacting us with your request. You can make request at the time of submission of your abstract.
PRE-WORKSHOP LECTURES FOR AIU STUDENTS AND GENERAL AUDIENCE WILL BE HELD ON FRIDAY, MAY 12, 2016, 17:00-19:00 IN LECTURE HALL BUILDING D.EVERYONE IS WELCOME!
ORGANIZING COMMITTEE:
Masami Hagiya (Tokyo University) hagiya@is.s.u-tokyo.ac.jp
Yasuhiro Suzuki (Nagoya University) ysuzuki@nagoya-u.jp
Marcin J. Schroeder (Akita International University) mjs@aiu.ac.jp
12th International Workshop on Natural Computing
May 26-27 (Saturday &Sunday), 2018Akita International University Akita JAPAN
SIGNAC, Japan Society of Artificial Intelligence
about the workshop
The series of International Workshops on Natural Computing initiated in 2006 grew up from the original interest in molecular computing. However, within the years following this original initiative the topic of natural computing became one of main directions of study in several disciplines. Natural processes or even entire life started to be considered a form of information processing with characteristics of computing. On the other hand, information processing in natural systems became a source of inspiration for innovation in computer science, artificial intelligence and engineering. Moreover, computer simulation became a common tool for study of nature.
Following this general trend of mutual interactions of disciplines the 12th International Workshop on Natural Computing continues already established tradition of the IWNC series to devote its sessions to the recent and future developments in research, practice, philosophical reflection and creative activity within the crossroads of nature, computing, information science, cognitive science, study of life and culture.
The intention of the workshop is to bring together a very wide range of perspectives from philosophical to scientific ones, to visions of artists. There will be an opportunity to present original and creative contributions without any restriction by disciplinary divisions or the level of advancement of research. Contributions from the beginning of the academic or intellectual career are as welcome as those from its peak.
We also invite informal and popular short presentations for students introducing non-specialists into the subject of the workshop which will be scheduled in the evening on Friday before the workshop.REGISTRATION:
Participants do not have to pay any registration fee, but they have to cover from own funds the cost of travel, accommodation, and of the optional social event (dinner). Registration for the workshop is necessary for the purpose of planning and logistics.
CALL FOR CONTRIBUTIONS (ABSTRACTS):
We invite submission of abstracts for intended presentations at the workshop. Abstracts should be in English and they should be sufficiently extensive to describe clearly the content of presented work, but their expected volume is within 200-500 words. The subject matter of presentations is not restricted to specific disciplines or topics, but the originality of the presented work and relevance to the main theme of the workshop is expected.
Contributed presentations are planned for 30 minutes including 20-25 minute lecture and 5-10 minute discussion.
EXTENDED DEADLINE for submissions: May 10, 2018. Acceptance notices will be sent soon after submitted abstracts are reviewed by organizers. Late submissions may be considered, but in order to secure full consideration, please meet the deadline. Submissions can be sent any time after this announcement to ysuzuki@nagoya-u.jp and/or mjs@aiu.ac.jp (we recommend sending your submissions to both addresses to ensure faster processing).
ACCOMMODATION:
Participants in the workshop may stay in Krypton Hotel (Official Guest Accommodation for AIU at the border of AIU campus) for discounted price of ca. 7,000 yen per night. However, to secure availability of accommodation at Krypton Hotel please consider making arrangements for reservation as early as possible by contacting us with your request. You can make request at the time of submission of your abstract.PAST WORKSHOPS IN THE IWNC SERIES:
1st, Dec 14-15, 2006 : University of West-England, Bristol, UK2nd, Dec 10-13, 2007 : Nagoya University, Nagoya, Japan
3rd, Sept. 23, 2008 : Yokohama National University, Yokohama, Japan4th, Spet, 23-19, 2009 ; Himeji International Exchange Center, Japan
5th, Sept, 21, 2010 ; Ascoli Piceno, in ACRI2010, ItalyMar, 15-16, 2011; as "Winter School of Hakodate", Future University Hakodate, Japan
6th, Mar, 28-30, 2012; Tokyo University, Tokyo, Japan
7th, Mar, 20-22, 2013; Tokyo University, Tokyo, Japan
8th, Mar, 18-19, 2014; YMCA, Hiroshima, Hiroshima, Japan
9th, Mar. 15, 2015; Tokyo University, Tokyo, Japan
10th, May 14-15, 2016; Akita International University, Akita, Japan
11th, May 13-14, 2017, Akita International University, Akita, JapanPRE-WORKSHOP LECTURES FOR AIU STUDENTS AND GENERAL AUDIENCE WILL BE HELD ON FRIDAY, MAY 25, 2016, 17:00-19:00 IN LECTURE HALL BUILDING D.
EVERYONE IS WELCOME! The schedule 17:00-19:00 is tentative and possible change to slightly later time in the evening may be announced later.ORGANIZING COMMITTEE:
Masami Hagiya (Tokyo University) hagiya@is.s.u-tokyo.ac.jp
Yasuhiro Suzuki (Nagoya University) ysuzuki@nagoya-u.jp
Marcin J. Schroeder (Akita International University) mjs@aiu.ac.jp
LOCAL ORGANIZING COMMITTEE at Akita International University
Florent Domenach fdomenach@aiu.ac.jp
Attila Egry-Nagy egri-nagy@aiu.ac.jp
Yasushi Nara nara@aiu.ac.jp