Search Results for "genetic algorithm java" - Page 9
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Showing 234 open source projects for "genetic algorithm java"
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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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GAPI (pronunced gappy) is the Genetic Algorithms Programming Interface - a set of Java classes that allow users to easily integrate Genetic Algorithms into their Java programs. See "GAPI specs" in the Feature Requests forum for more info.
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TA scheduler based on a genetic algorithm to make the tedious task of scheduling TA's more efficient.
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Unit tests-based Genetic Programming in Java. The developer specifies unit tests, and the tool will use GP to evolve software that passes those tests.
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Jeep is a modular, abstract and distributed evolutionnary programming core written in Java, allowing to grow autonomous agents as well a gene pool (as in genetic algorithms).
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jrgp is a strong-typed Genetic Programming system, which features a graphical interface (gool) to setup and run GP-problems and a tool (fs-d) that greatly simplifies the definition of a GP-problem.
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Automated MapMaker for the Diplomacy boardgame. Using Genetic Algorithms and some user-defined criteria, DipMap will try to generate a playable Diplomacy map.
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OpenAI is dedicated to creating a full suite of highly interoperable Artificial Intelligence components that make the best use of today's technologies. Current tools include Mobile Agents, Neural Networks, Genetic Algorithms and Finite State Machines.
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GD is AI - ALife becoming true. It's a genetic engine server, capable to run any kind of genetic algorithm. It has TCP architetcure, working with software clients and uman interaction. It has plugin capabilities and comes with a working Function Finder
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Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.
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ga2 is a simple C++ library providing the necessary base classes to implement a genetic algorithm in C++. It is based loosely on Goldberg's canonical GA, but with many modifications, improvements and additional features. Essentially feature-complete, and
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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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GenP Genetic Programming Library is a cross-platform library of genetic programming functions for generic application. Initially it's purpose is for machine learning in board games but should be applicable to any purpose.
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The goal of the Rats and Mazes project is to build a simple genetic algorithm to find general solutions to random non-cyclic single path mazes. I believe that the solutions will tend towards either the right/left-hand rule.
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aVolve is an evolutionary/genetic algorithm designed to evolve single-cell organisms in a micro ecosystem. It currently uses the JGAP Genetic algorithm, but does include a primitive genetic algorithm written in Python.
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This is a very simple implementation of the genetic algorithm framework presented by John Holland, based on Goldberg book Genetic Algorithms in Search, Optimization and Machine Learning.
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This simplesudodu program is intend for studying in the sudoku solution algorithm rather than a game (If you want to make it a game, it's OK ^_^). Later I will implement the 4*4 or other kinds. Different sudoku requires different algorithm to solve.
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GAZES - Genetic Algorithm Zombie Eradication Simulation Grid-based simulator for zombie scenario. The units will use genetic algorithm to determine their actions on a cycle by cycle basis. This is a school project, so is likely on hiatus for summer.
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GENet
A genetic algorithm framework for artificial neural networks.
A genetic algorithm framework to allow the evolution of synapse weights and topologies of artificial neural networks. -
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This project aims at using the Artificial Intelligence (AI) algorithm called the Genetic algorithm to solve the problem of placement in the FPGA circuits.
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Integer Singular Value Decomposition Genetic Algorithm Function Fitter. This is an optimization algorithm that performs a similar role to a neural network.
