GNU/Linux AI & Alife HOWTO - John Eikenberry (best mystery novels of all time txt) 📗
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general traits of living systems (such as self-organization),
and other issues pertaining to theoretical or evolutionary
biology and dynamic systems.
breve
� Web site: www.spiderland.org/breve/
breve is a free software package which makes it easy to build 3D
simulations of decentralized systems and artificial life. Users
define the behaviors of agents in a 3D world and observe how
they interact. breve includes physical simulation and collision
detection so you can simulate realistic creatures, and an OpenGL
display engine so you can visualize your simulated worlds.
BugsX
� FTP site:
http://surf.de.uu.net/zooland/download/packages/bugsx/
Display and evolve biomorphs. It is a program which draws the
biomorphs based on parametric plots of Fourier sine and cosine
series and let’s you play with them using the genetic algorithm.
Creatures Docking Station
� Linux info: sylv.inkwell.com.ru
This is a free version of the Creatures3 ALife game. It has
fewer species and a small ‘space-station’ world, but can connect
to other worlds over the internet and (if you have the windows
version of the game) can connect to your C3 world. The game
itself revolves around breeding and training the alife
creatures, ‘Norns’. Its strikes a pretty nice balance between
fun and science, or so I’m told.
(summary written by Steve Grand included below)
The eponymous creatures in this computer game are called Norns,
and the world’s population of them at one stage hovered around
the five million mark, making them more common than many
familiar natural species. Each norn is composed of thousands of
tiny simulated biological components, such as neurons,
biochemicals, chemoreceptors, chemoemitters and genes. The
norns’ genes dictate how these components are assembled to make
complete organisms, and the creatures’ behaviour then emerges
from the interactions of those parts, rather than being
explicitly ‘programmed in’.
The norns are capable of learning about their environment,
either by being shown things by their owners or through learning
by their own mistakes. They must learn for themselves how to
find food and how to interact with the many objects in their
environment. They can interact with their owners, using simple
language, and also with each other. They can form relationships
and produce offspring, which inherit their neural and
biochemical structure from their parents and are capable of
open-ended evolution over time. They can fall prey to a variety
of diseases (as well as genetic defects) and can be treated with
appropriate medicines.
dblife & dblifelib
� FTP site: ibiblio.org/pub/Linux/science/ai/life/
dblife: Sources for a fancy Game of Life program for X11 (and
curses). It is not meant to be incredibly fast (use xlife for
that:-). But it IS meant to allow the easy editing and viewing
of Life objects and has some powerful features. The related
dblifelib package is a library of Life objects to use with the
program.
dblifelib: This is a library of interesting Life objects,
including oscillators, spaceships, puffers, and other weird
things. The related dblife package contains a Life program
which can read the objects in the Library.
Drone
� Web site: www.cscs.umich.edu/Software/Drone/
Drone is a tool for automatically running batch jobs of a
simulation program. It allows sweeps over arbitrary sets of
parameters, as well as multiple runs for each parameter set,
with a separate random seed for each run. The runs may be
executed either on a single computer or over the Internet on a
set of remote hosts. Drone is written in Expect (an extension to
the Tcl scripting language) and runs under Unix. It was
originally designed for use with the Swarm agent-based
simulation framework, but Drone can be used with any simulation
program that reads parameters from the command line or from an
input file.
EcoLab
� Web site: parallel.hpc.unsw.edu.au/rks/ecolab/
EcoLab is a system that implements an abstract ecology model. It
is written as a set of Tcl/Tk commands so that the model
parameters can easily be changed on the fly by means of editing
a script. The model itself is written in C++.
Game Of Life (GOL)
� FTP site: ibiblio.org/pub/Linux/science/ai/life/
GOL is a simulator for conway’s game of life (a simple cellular
automata), and other simple rule sets. The emphasis here is on
speed and scale, in other words you can setup large and fast
simulations.
gant
� Web site: gant.sourceforge.net
This project is an ANSI C++ implementation of the Generalized
Langton Ant, which lives on a torus.
gLife
� Web site: glife.sourceforge.net
� SourceForge site: sourceforge.net/projects/glife/
This program is similiar to “Conway’s Game of Life” but yet it
is very different. It takes “Conway’s Game of Life” and applies
it to a society (human society). This means there is a very
different (and much larger) ruleset than in the original game.
Things need to be taken into account such as the terrain, age,
sex, culture, movement, etc
Golly
� Web site: golly.sourceforge.net
An open source, cross-platform implementation of John Conway’s
Game of Life with an unbounded universe and capable of running
patterns faster and further than ever before. It has many
features such as;
� Reads RLE, Life 1.05/1.06, and macrocell formats.
� Supports Wolfram’s 1D rules.
� Can paste in patterns from the clipboard.
� Scriptable via Python.
Langton’s Ant
� Web site: www.theory.org/software/ant/
Langton’s Ant is an example of a finite-state cellular automata.
The ant (or ants) start out on a grid. Each cell is either black
or white. If the ant is on a black square, it turns right 90
and moves forward one unit. If the ant is on a white square, it
turns left 90 and moves forward one unit. And when the ant
leaves a square, it inverts the color. The neat thing about
Langton’s Ant is that no matter what pattern field you start it
out on, it eventually builds a “road,” which is a series of 117
steps that repeat indefinitely, each time leaving the ant
displaced one pixel vertically and horizontally.
LEE
� Web site: www.informatics.indiana.edu/fil/LEE/
LEE (Latent Energy Environments) is both an Alife model and a
software tool to be used for simulations within the framework of
that model. We hope that LEE will help understand a broad range
of issues in theoretical, behavioral, and evolutionary biology.
The LEE tool described here consists of approximately 7,000
lines of C code and runs in both Unix and Macintosh platforms.
MATREM
� Web site: www.phys.uu.nl/~romans/
Matrem is a computer program that simulates life. It belongs to
the emerging science of “artificial life”, which studies
evolution and complex systems in general by simulation. Matrem
is also a game, where players compete to create the fittest
lifeform. Their efforts are the driving force behind the
program.
Noble Ape
� Web site: www.nobleape.com/sim/
The Noble Ape Simulation has been developed (as the Nervana
Simulation) since 1996. The aim of the simulation is to create a
detailed biological environment and a cognitive simulation. The
Simulation is intended as a palette for open source development.
It provides a stable means of simulating large scale
environments and cognitive processes.
For MacOS Classic and X, with Java, Windows and Linux(Motif)
versions in beta. Features a non-polygonal graphics engine
(Ocelot) and a command-line version
POSES++
� Web site: www.gpc.de/eindex.html
The POSES++ software tool supports the development and
simulation of models. Regarding the simulation technique models
are suitable reproductions of real or planned systems for their
simulative investigation.
In all industrial sectors or branches POSES++ can model and
simulate any arbitrary system which is based on a discrete and
discontinuous behaviour. Also continuous systems can mostly be
handled like discrete systems e.g., by quantity discretion and
batch processing.
Tierra
� Web site: www.his.atr.jp/~ray/tierra/
Tierra’s written in the C programming language. This source code
creates a virtual computer and its operating system, whose
architecture has been designed in such a way that the executable
machine codes are evolvable. This means that the machine code
can be mutated (by flipping bits at random) or recombined (by
swapping segments of code between algorithms), and the resulting
code remains functional enough of the time for natural (or
presumably artificial) selection to be able to improve the code
over time.
Trend
� Web site: www.complex.iastate.edu/download/Trend/
Trend is a general purpose cellular automata simulation
environment with an integrated high level language compiler, a
beautiful graphical user interface, and a fast, three stage
cached simulation engine. This is the simulation system that was
used to discover the first emergent self-replicating cellular
automata rule set, and the first problem solving self-replication loop.
Since its simulator is very flexible with regard to cellular
space sizes, cell structures, neighborhood structures and
cellular automata rules, Trend can simulate almost all one or
two-dimensional cellular automata models. It also has a smart
backtracking feature which simplifies rule set development a lot
by allowing users to go back to a previous stage of simulation!
With other advanced features, Trend is probably the most easy to
use 2-dimensional cellular automata simulator.
Also available is jTrend. A Java version of Trend.
XLIFE
� FTP site: surf.de.uu.net/zooland/download/packages/xlife/
This program will evolve patterns for John Horton Conway’s game
of Life. It will also handle general cellular automata with the
orthogonal neighborhood and up to 8 states (it’s possible to
recompile for more states, but very expensive in memory).
Transition rules and sample patterns are provided for the
8-state automaton of E. F. Codd, the Wireworld automaton, and a
whole class of `Prisoner’s Dilemma’ games.
Xtoys
� Web site: thy.phy.bnl.gov/www/xtoys/xtoys.html
xtoys contains a set of cellular automata simulators for X
windows. Programs included are:
� xising – a two dimensional Ising model simulator,
� xpotts – the two dimensional Potts model,
� xautomalab – a totalistic cellular automaton simulator,
� xsand – for the Bak, Tang, Wiesenfeld sandpile model,
� xwaves – demonstrates three different wave equations,
� schrodinger – play with the Scrodinger equation in an
adjustable potential.
6. AgentsAlso known as intelligent software agents or just agents, this area of
AI research deals with simple applications of small programs that aid
the user in his/her work. They can be mobile (able to stop their
execution on one machine and resume it on another) or static (live in
one machine). They are usually specific to the task (and therefore
fairly simple) and meant to help the user much as an assistant would.
The most popular (ie. widely known) use of this type of application to
date are the web robots that many of the indexing engines (eg.
webcrawler) use.
3APL
� Web site: www.cs.uu.nl/3apl/
� Wikipedia entry: en.wikipedia.org/wiki/3APL
� Mobile version: www.cs.uu.nl/3apl-m/
3APL is a programming language for implementing cognitive
agents. It provides programming constructs for implementing
agents’ beliefs, goals, basic capabilities (such as belief
updates, external actions, or communication actions) and a set
of practical reasoning rules through which agents’ goals can be
updated or revised. The 3APL programs are executed on the 3APL
platform. Each 3APL program is executed by means of an
interpreter that deliberates on the cognitive attitudes of that
agent.
Agent
� FTP site: www.cpan.org/modules/by-category/23_Miscellaneous_Modules/Agent/
The Agent is a prototype for an Information Agent system. It is
both platform and language independent, as it stores contained
information in simple packed strings. It can be packed and
shipped across any network with any format, as it freezes itself
in its current state.
agentTool
� Web site: macr.cis.ksu.edu/projects/agentTool/agentool.htm
� Download site:
macr.cis.ksu.edu/projects/agentTool/registration.htm
Another Java based agent development framework. Fairly unique in
that it emphasizes the use of a GUI for designing the system
which will “semi-automatically synthesize multiagent systems to
meet
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