Showing 25 open source projects for "framework"

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  • 1
    Evolutionary Computation Framework

    Evolutionary Computation Framework

    C++ framework for application of any type of evolutionary computation.

    ECF is a framework intended for application of any type of evolutionary computation (GA/GP, DE, Clonalg, ES, PSO, ABC, GAn, local search...). It offers simplicity for the end-user (parameterless usage, tutorial) and customization for experienced EC practicioners.
    Downloads: 2 This Week
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  • 2
    jMetal
    jMetal is an object-oriented Java-based framework for solving multi-objective optimization problems with metaheuristics.
    Downloads: 4 This Week
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  • 3
    Opt4J

    Opt4J

    Modular Java framework for meta-heuristic optimization

    Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary meta-heuristic optimization algorithms. ...
    Downloads: 0 This Week
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  • 4

    serein

    A Framework to Model Metaheuristics

    Downloads: 0 This Week
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  • 5
    JCLEC
    JCLEC is a general purpose evolutionary computation framework developed in Java. Some of its mains features are: multilevel architecture, highly reusable and integrable with other systems, easy to use and a lot of implemented algorithms and operation
    Downloads: 0 This Week
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  • 6
    SEAGE
    Search Agents - a framework for collaboration of meta-heuristic agents
    Downloads: 0 This Week
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  • 7

    Genetic Basis

    A general genetic algorithm framework

    Downloads: 0 This Week
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  • 8

    ACOptim

    Ant Colony Optimizer

    Simple POSIX multithread Ant Colony Optimizer framework currently for solving Vehicle Routing Problem. Supports UDP, file synchronizatoin between computers.
    Downloads: 0 This Week
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  • 9
    Framework for development of simple evolutionary algorithms / island models programs in distributed environment using MapReduce programming model based on hadoop.
    Downloads: 0 This Week
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  • 10
    Sleepwalker aims to provide a highly abstract, universal, reusable, extensible Java-based genetic algorithms framework which can be used as a basis for modelling and programming virtually any practical optimisation problem.
    Downloads: 0 This Week
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  • 11
    X-GAT
    X-GAT (XML-based Genetic Algorithm Toolkit) is a Java framework to optimize problems with Genetic Algorithms (GAs). Differently from other frameworks, X-GAT contains ready-to-use GAs implementations and new features can be easily added.
    Downloads: 0 This Week
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  • 12
    Based on the introduction of Genetic Algorithms in the excellent book "Collective Intelligence" I have put together some python classes to extend the original concepts.
    Downloads: 0 This Week
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  • 13
    EasyGenetic is a highly efficient C++ framework for genetic master-slave algorithms. It heavily makes use of template metaprogramming to provide a fully customizable environment that accommodates most of user's needs without sacrificing efficiency.
    Downloads: 0 This Week
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  • 14
    CILib is a framework for developing Computational Intelligence software in swarm intelligence, evolutionary computing, neural networks, artificial immune systems, fuzzy logic and robotics.
    Downloads: 0 This Week
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  • 15
    A .net implementation of a framework for genetic algorithms. This tool enables programmers to write the "core" of their problem and have a genetic algorithm immediately setup for solving it.
    Downloads: 0 This Week
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  • 16
    Very useful framework library, contains many frequent used code snippets, algorithms, data structures, WinForms & APS.NET controls for all-day work.
    Downloads: 0 This Week
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  • 17
    The Gene Expression Programming Framework in Java. It separates the process of evolution from the process of interpretation of the chromosome, allowing the use of various schemes in the chromosome.
    Downloads: 0 This Week
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  • 18
    The Distributed Genetic Programming Framework is a scalable Java genetic programming environment. It comes with an optional specialization for evolving assembler-syntax algorithms. The evolution can be performed in parallel in any computer network.
    Downloads: 0 This Week
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  • 19
    A framework for utilising the Genetic Algorithm in the domain of Game Theory
    Downloads: 0 This Week
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  • 20
    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.
    Downloads: 0 This Week
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  • 21
    Simple genetic programming framework. Features a robust set of interfaces and standard implementations for rapid development and ease of experimentation.
    Downloads: 0 This Week
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  • 22
    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.
    Downloads: 0 This Week
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  • 23
    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.
    Downloads: 0 This Week
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  • 24
    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.
    Downloads: 0 This Week
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  • 25

    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.
    Downloads: 0 This Week
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