Search Results for "parallel genetic algorithm" - Page 11
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Showing 319 open source projects for "parallel genetic algorithm"
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A concise example of the classical genetic algorithm, with a fancy windows terminal display. Features DNA editing, save/load, customizable constraints and statistics logging.
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gaDesignLib
Genetic algorithm for mechatronic product design
This C++/STL library provides you with the basic genetic algorithms needed for engineering design, such as simple GA and variable population. -
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This project aims to improve the Civilization 4 AI using a genetic algorithm. We also have some alternative AI algorithms which have been custom written that will hopefully also improve the AI.
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DrPangloss is a python implementation of a three operator genetic algorithm, complete with a java swing GUI for running the GA and visualising performance, generation by generation
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NullAllEst is the implementation of a maximum likelihood algorithm to estimate the frequency of a null allele in microsatellite genetic data. A Markov Chain Monte Carlo simulation is used to solve the likelihood function.
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A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.
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OGA, Open Genetic Algorithm implements the evolutionary genetic algorithms with an user interface in GTK+. The main goal of the program is solve complex problems using evolutionary algorithms like genetic algorithms or evolutionary strategies.
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Galapagos is a Genetic Algorithm framework written in Java 5 with the intended audience of undergraduates in an Artificial Intelligence class. The goal of Galapagos is usability: a competent student should be able to learn this library in an afternoon.
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NeuroDraughts is a Draughts/Checkers game that teaches itself how to play through self play. It combines an Artificial Neural Network, trained by Temporal Difference Learning using some Genetic Algorithm style behaviour.
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musicomp is a program which most important element is an evolutionary algorithm which uses data mining methods as a fitness function to generate monophone melodies.
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Genetic Algorithm based software to resolve the Traveling Salesman Problem (Problema del Commesso Viaggiatore).
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Neural networks evolution (genetic algorithm) written in Java. Now neural networks try to playing Go, Tic-Tac-Toe.
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Molevolve is a Java library for running a Genetic Algorithm to model the 3-dimensional structures of peptide chains from amino-acid sequences. Client code can specify its own peptide chain model, fitness functions and GA operations. Requires JDK 1.5.
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unEvo is an Eclipse plug-in that provides support for the experimentation and research process on Evolutionary Algorithms, intended so that the user can implement an evolutionary algorithm without lost time in the code of the algorithm.
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The project´s name is Generic Genetic Algorithm, Its an application that permits the use of a genetic algorithm skeleton to solve a problem. The language is python. The os Debian. The objective is to unify genetic algorithm practices in a generic aplicat
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Black Box GA provides a user, with a black box program to use a genetic algorithm to help optimize problems, without the user coding a genetic algorithm, or even understanding how a Genetic Algorithm works!
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MPIGALib is a parallel genetic algorithms library built on Mathew Walls GALib and MPI that allows genetic algorithm enthusiasts and researchers to parallelize there serial genetic algorithm implementations.
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EasyAI is a project to build classical AI program and method in Java language, such as resolution for logic, greedy search, genetic algorithm, neural network and so on...
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IslandEv distributes a Genetic Algorithm (like <a href="/projects/jaga">JaGa</a>) across a network (see <a href="/projects/distrit">DistrIT</a>) using an island based coevolutionary model in which neighbouring islands swap migrating individuals every
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GALib, Java Genetic Algorithm (JAR) library, models chromosomes as real numbers, characters, strings, and string sequences. Very easy to use, just extend one of the existing GA classes and implement your fitness function. Sample GAs included.
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C++ genetic algorithms library (solving of the NP opnimisation problems). More GA strategies, more useability, more algorithm speed.
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STAR, stand-alone advanced c++ algorithm library, addressing mathematical/statistical problems, genetic algorithms, and a framework of system functions (including, but not limited to, XML parsing and writing, sorting, hashing, etc.)
