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An implementation of the Compositional Pattern Producing Networks (CPPNs) and Neuro-Evolution of Augmenting Topologies (NEAT) proposed by Kenneth O. Stanley, based on the Genetic Art tool from Mattias Fagerlund.
JLife is a Java framework for testing and playing with A-Life.
The the main idea is about evolving creatures, that consists of chain of commands, that influence both the creature and it's environment.
Project Genesis brings the game of life up-to-date. instead of dots, we have animals, instead of trivial rules about close proximity dots, we model real world activities: move,eat,kill,steal,destroy,sleep, breed and learn different patterns of behavior.
A game/toy that simulates a world environment with organisms to survive: game of life with more complex rules. Every programmer can make his/her own organisms and compete with others. Hopefully in the future it will support genetics.
ANJI
(Another NEAT Java Implementation)
Built on top of existing OpenSource projects, ANJI is an implementation of NEAT (Neuro-Evolution of Augmenting Topologies), an algorithm for evolving artificial neural networks.
Kandid generates images using genetic algorithms. In a simulated evolution surprising images can be found calculated with Lisp expressions, Textures, Iterated Function Systems, Linear Cellular Automata, Voroni diagrams, Lindenmayer Systems and POVray
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Agentbeats - A music generator experiment with the purpose of creating rhythms and melodies using artificial intelligence/life and connexionist paradigms.
The Generation5 Java Development Kit (JDK) enables users to create demonstration programs and applets for a wide variety of Artificial Intelligence and ArtificialLife paradigms.
Set of Java packages to apply Genetic Algorithms to any kind of problem. Various genetic operators are implemented and an example shows of how the system could be applied to digital circuit evolution.
Java based system for creating Bio-Musical Worlds. Investigating the use of AI (flocking,A-Life, Genetic Algorithms, Neural Networks) and other bio-modelling techniques for the creation and evolution of musical landscapes.
Solving the travelling salesman problem with genetic (evolutionary) algorithms. The distance calculations are based on geographical coordinates. The progress of the algorithm is visualized with a geo-map and some statistics.
An Evolution Simulator of Single Cells in a Pond. This shows a crosssection of
water with sun shining from above. A single cell is dropped in and has various genes. The cells multipy and evolve. See Files above for download and screenshot.
This is a artificiallife project.
the goal is to simulate the evolution of micro-organisms.
It uses neural networks to simulate the brain of each of those micro-organisms.
It's written in JAVA, and uses the Joone librarie
This projects intends to develop a complete distributed peer-to-peer environment
for running heuristic optimization, modelling, artificiallife, etc applications. This involves a network engine, libraries and different user interfaces. All this in java.
The Athlete is a virtual robot living in the ODE (Open Dynamics Engine)world. An evolution algorithm is implemented based on the DR-EA-M to optimize its performances. This involves a Genetic algorithm, network of neurons and morphology. All is in java.
Gnubert will be a system to use the power of many computers across the internet to solve problems using evolutionary techniques. Any user may define a problem and the system will attempt to solve it.
This project aims to build a full featured C++ (and possibly Python) library and associated tools which facilitate building ArtificialLife simulations in a distributed environment.
This description is going to change and intent of the project will be refocused. This is Tierra-like artifical life program simulation system written in Java. I'm hoping to attract other developers to work on this little interesting project.
Domigene is a genetic algorithm API attempting to incorporate dominant and recessive genes. Supports modular evolution types, genetic programs, definable instruction sets, variation in population, chromosomes, mortality, mutation, fitness functions.