Search Results for "genetic algorithms" - Page 7
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Showing 184 open source projects for "genetic algorithms"
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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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EvoTrader is a stock picking platform that utilizes genetic programming to evolve rules for generating stock trading signals.
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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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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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A library for Cartesian Genetic Programming (CGP.) This project includes a simple Evolution Strategy library that can be used for evolution.
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This project's goal is to implement Artificial Inteligence algorithms and make them available for any platform but especially for mobile devices. The main objective is to allow the community to develop better and more inteligent mobile games.
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Simple genetic programming framework. Features a robust set of interfaces and standard implementations for rapid development and ease of experimentation.
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This project aims at providing a set of tools for solving the class of monodimensional packing problems (such as cutting stock, bin packing and knapsack problem) mainly using genetic algoritms.
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The Airs GPT project experiments with Steady State Genetic Programming create agents that play tag. It emphasises co-evolution through competition, and provides the user with some tools to help them visualize what is taking place.
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MAIF is developed in Java 5 (especially Generics) and aims at building AI algorithms, by concentrating onto the mapping of real-world problems, while abstracting from their inner working. It can be extended with new algorithms and problem representations.
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Mr. Logister is a resource scheduling application that uses genetic algorithms to find the best utilization and allocation of resources. The scheduler understands hard constraints like free/busy time and soft constraints like suitability and preferences.
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Formicidae is the official simulator and visualizer for the Ant-Wars competitive programming site, written in Java and SISC. The site is hosted at www.ant-wars.net.
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Amygdala is a C++ spiking neural network library. It includes several neuron models, SMP support and facilities for developing SNNs with genetic algorithms. Support for running Amygdala neural networks on workstation clusters and MPPs is also under way
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This is an attempt to use Genetic Programming for writing a go player in a pseudo-ASM. It is entirely written in Common Lisp.
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A java framework for developing meta-heuristics that supports the use of grids environments. The meta-heuristics planned to be realeased are GAs, VNS and NNs. The grid middleware that will be firstly explored is the OurGrid solution.
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It moves by itself inside networks like virus infection & plagues, it is being written to solve computer virus problem drastically and responsibly. It is legal, free and open for public domain to improve W3 ICT Security.
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This is a cross-platform framework for using Genetic Algorithms for solutions. Written in Java and uses convinient plug-in features for every phase in the genetic development, while maintaining an easy-to-use API for easy integration into applications.
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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 Genetic Algorithms Package (GAlg) is a highly-extensible, simple, and easy to understand implementation of genetic algorithms in 100% Java.
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Galileo is a library for developing custom distributed genetic algorithms developed in Python. It provides a robust set of objects that can be used directly or as the basis of derived objects. Its modularity makes it easy to extend the functionality. The
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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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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.