Complex Systems and ALife Created by Cellular Automata
(Java applets and many related links)
by Tomoaki SUZUDO
(Japanese is here)
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The icons for hyperlinks:
: A newly added information
: An excellent link
: A cellular automaton demo using applets
What's new?
New conference
ACRI 2006 Seventh International conference on Cellular Automata for Research and Industry, September 20-23, 2006
Download
My gear for complexity research is a Java program of a 2-dimensional cellular automata tool, called Cambria (was called CADemo). As you see below, anyone can download my program including source codes. If you have a problem to decompress this file or want another compression format, please contact the Webmaster.
and my old gear. ( Warning!! I'm no longer maintaining this program as 2D CA is too slow. As the source code is available, please use this not for a complete tool but programming ingredients.)
JAVA-applet demos of Cellular Automata (CAs)
All the the demos you see here work on 2 dimensional (2D) space. In fact, 2D CAs are most commonly used by CA researches. This is probably because 1D CA cannot produce various self-organized patterns of interest, and also it is difficult to show 3D CAs on the computer screen. The applet runs on Internet Explorer 4.0 (or later) or Netscape 4.0 (or later) in Win32, and Internet Explorer 4.0 (or later) in Macintosh. Netscape 4.72 on Intel/Linux seems OK. If the picture gets broken, select slower updating from preference button.
I want to remind you that the sign of
means a direct link to the applet demo. If you do not know where to start, please try the first applet 'Aquarium' which is a set of my original CAs designed for Alife study.
- aqua.html: Aquarium
![[demo]](demo.gif)
This class of cellullar automata was designed for simulating prey-predator interaction. I realized these cellular automata create many gliders like little creatures. You can try the preset rules or set your own rule. To change the default rule, click "rule" button. The available preset rules are:
- Pond: This is the most basic example of Aquarium rule. It looks many little creature are swimming in a pond.
- Lake: Similar to Pond, but you see larger creatures than Pond creates.
- Plankton: Similar to Pond, but little creatures look like plankton rather than fish.
- Tanks: Similar to Pond, but little creatures look like tank rather than fish.
- Birds: Looks like patterns formed by migratory birds
- Typhoon: Starting from peaceful Pond-like pattern, but later everything is swallowed by developing vortex.
- Galaxy: Similar to Typhoon, but the growth of the vortex is limited, and sometimes it collapses. In Galaxy, any red cells can not survive when at least one of the neighbors is red. This is added to Typhoon's rule.
- Wave: Similar to Typhoon, but the vortex is not stable and may suddenly die.
- Honeycomb: Coexistence of regular and chaotic parts is quite intriguing.
- aquaP2.html: AquariumP2
![[demo]](demo.gif)
This is an extention of Aquarium rule. In this design, predator has a bit longer life and the gliders become a bit more complicated.
- crystal.html: A simple crystallization
![[demo]](demo.gif)
If the rule is selected such that the system is at the critical point between static one and chaotic one, the crystallization may appear. At such critical point, only few microscopic patterns are stable and the rest patterns are gradually eliminated from the space. Crystallization is the simplest example of self-organization and self-replication at the edge of chaos. See the detail at ref. [Su99].
- crystal3a.html: Crystal3a
![[demo]](demo.gif)
a little complicated crystallization. You need more state-per-cell to create more complicated pattern.
- crystal3b.html: Crystal3b
![[demo]](demo.gif)
Another a-little-more-complicated crystallization.
- aggre.html: Aggregation
![[demo]](demo.gif)
A different type of crystallization using 3 state-per-cell. It looks like an aggregating phenomenon.
- colony.html: Colony
![[demo]](demo.gif)
As time passes, a stable pattern spreads over the space.
- butterfly.html: Butterfly
![[demo]](demo.gif)
It looks like the self-replication of butterflies.
- knitting.html: Knitting
![[demo]](demo.gif)
You can see many chains which are sometimes destroyed and generated.
What I am trying to do now is to establish a more realistic simulation of artificial chemistry. The first thing I abandoned was the synchronous update over the whole space. This change removes the patterns dependent on the synchronous update which is not essential to chemical dynamics. The second change was to introduce the mass preservation. This is, needless to say, essential to realistic chemical simulations. For this purpose I adopted a partitioning scheme.
The following are imported rules. This is not a comprehensive list, just the ones I like.
[Cr83] Creutz, M. "Microcanonical Monte Calro Simulation'", 1983 Phys. Rev. Let. , 50-19, 1411-1414.
[De89] Dewdney A. K. "Computer recreations", 1989 Sci. Am., 261August, 102-105.
[Fi90] Fisch, R.. "Cyclic cellular automata and related process", Physica
D 45, 19-25 (1990).
[Ga70] Gardner, M. "Mathematical games", 1970 Sci. Am., 223 October,
120-123.
[Ga71] Gardner, M. "Mathematical games", 1971 Sci. Am., 224 February, 112-117.
[La84] Langton, C. G. "Self-reproduction in cellular automata", Physica D, Vol. 10, 135-144(1984).
[Su99] Suzudo, T. "Crystallisation of two-dimensional cellular automata", Complexity International,Vol. 6 (1999). to download pdf-formatted file
Tutorial sites
Downloadable tools and demonstrations
Online Papers
- Mitchell M. et al. "Revisiting the edge of chaos: evolving cellular automata to perform computations", Complex Systems, 7, 89-130, 1993.(online paper)
- Wolfram, S. "Statistical mechanics of cellular automata" , Rev. Mod. Phys. 55 (1983), 601-644. (Online paper)
- Wolfram, S. "Universality and complexity in cellular automata", 1984 Physica D, 10, 1-35. (Online paper)
The origin of life is mysterious. Obviously life was created from inanimate objects, and is composed of them. We know each molecular is not life, but they gain mind or an intention once they organize certain patterns.
One of the fundametal question on life is whether we can create life, for instance, on our computers? A computer with mind sounds like a science fiction and it is natural to suspect the possibility of artificial life, but many people are seriously triying to solve this problem.
This problem starts with discussing what kinds of capacity we have to give computers to be life. You may make the list of common properties every living organism has, but it is not obvious what are essential and what are not to be life. One of the possible ways to answer this question is to imagine what are necessary for the origin of life or primodal life. I think it is possible to narrow down the list to a few properties. The first one is self-replication. Without this, any species cannot survive. The second one is evolution. This simply means ability to change. Without this any living organism cannot adapt to a new environment. Earlier I thought only these two were necessary, because it seemed any primitive self-replication system with the evolution capacity could survive and become intelligent life. On computers, however, people already succeeded to make some modest self-relication and evolution. Even if you put them together, it does not seem to evolve into life with mind. I wondered what are missing.
Another prominent property of life is redundancy. For instance, a damage of a part of DNA is mostly compensated by another parts. It seems genes are organizing a network, and the production of necessary protain is guaranteed by many ways. Life is amazingly robust. What made or can make life so rubust? This is, I reckon, self-organization. The important thing is that the two essential abilities described above, to self-replicate and to evolve, were not given by anybody, but spontaneously acquaired. Thus these capacities of life are robust. So the third property is rubustness of the two properties. Consequently, I believe that to create life is to create self-organized self-replication and self-organized evolution, but nobody knows how to do it.
Related links are :
- Lotus Artificial Life
Interesting Applets
- ALife Online
A comprehensive alife information
- Zooland
![[good]](good.gif)
Great collection of ALife links
- Artificial Life and Complex Systems Page at the Chair of System Analysis, Department of Computer Science, University of Dortmund(Dead?)
- The MIT Press Journal: Artificial Life
- International Society of Artifitial Life
- Artificial
Life Page of Brunel Uinv. United Kingdom
- Calresco (Complexity and Artificial
Life Research Concept)
- Artificial Life Bibliography of On-line Publications by Ezequiel A Di Paolo
- Introduction of ALife by S. R. Ladd
- Digital Biology
Creating artificial lives that exhibit adaptive behavior
- Open Directory Project -Artificial Life
Links related to ALife
- FRAMSTICKS. Artificial Life
A three-dimensional life simulation project
- Tim's evolution page
Several applets related to artificial evolution
- The DCU Artificial Life Laboratory
Introduction of ALife Lab. in Dublin City University
- Origin and Evolution of Life on Earth
Essay about origin of life
- Thomas Ray's Tierra
Notorious Alife program
- Artificial Life: Evolutionary computation, emergence, learning by selection, social simulation, learning and agents, robotics, etc.
- Artificial Life by Mike Polowick Easy-to-read essay about Alife
- Boids (Flocks, Herds, and Schools) A famous ALife program
- news: comp.ai.alife
Newsgroup for Alife
- Genesis: Alife applet
- The Swarm Simulation System
![[good]](good.gif)
A software package for multi-agent simulation of complex systems
- Keith Wiley's Alife software
Downloadable original Alife simulation programs for Macintosh
- Jeffrey Ventrella's Page
Download of Alife softwares for Windows such as Gene Pool and Darwin Pond
- Alife Guide - Created by Stewart Dean
Kind and thorough introduction to artificial life
Chaos, fractal and nonlinear science links
The webmaster
Dr. Tomoaki Suzudo
Research Group for Advanced Reactor Systems
Japan Atomic Energy Research Institute
Tokai-mura, Naka-gun, 319-1195, JAPAN
Publications related to cellular automata for complex systems
- Suzudo, T. "Spatial Pattern Formation in Asynchronous Cellular Automata with Mass Conservation", to be publiched in Physica A, 343C, 185(2004) (to download pdf-formatted file)(296kB)
- Suzudo, T. "Searching for Pattern-Forming Asynchronous Cellular Automata
- An Evolutionary Approach", Proc. of ACRI2004, Lecture Note in Computer Science. (to download pdf-formatted file)(272kB)
- Suzudo, T. "Diversity of complex systems produced by a class of cellular automata", 6th International Conference on Complex Systems (CS02), Tokyo, September (2002). (to download pdf-formatted file)(1,113kB)
- Suzudo, T. "Crystallisation of two-dimensional cellular automata", Complexity International, Vol. 6 (1999). (Online paper) (to download pdf-formatted file, 412kB)
- Suzudo, T. "The entropy trajectory: A perspective to classify complex systems", Int. Symp. Frontier of Time Series Modeling, Tokyo, February, P008, (2000). (to download pdf-formatted file of the paper)(116kB)
(to download pdf-formatted file of the poster)(240kB)
Please let me know your WWW sites or software tools of cellular automata generating complex and life-like patterns. They may be listed here and linked to my Japanese CA related page. Recommending someone's useful sites or softwares are also welcome.
The E-mail address of the webmaster is
tsuzudo_at_qb3.so-net.ne.jp (Replace _at_ with @).
Note that I do not read any mail with an attached file or more.
Last modification on 17 January, 2004