Search Results for "artificial evolution" - Page 2
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Showing 35 open source projects for "artificial evolution"
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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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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.
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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.
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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.
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Pond Scum
Evolution Simulator.
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. -
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This is a artificial life 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
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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.
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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.
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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.
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Agentbased simulation of a real world evolution situation with Fox, Rabbit and Carrots in competition for life ressources.
