Showing 59 open source projects for "java framework"

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  • 1
    Currently, all existing formal tools are designed to serve as formal verifiers, using one implementation or another. NO tool is providing a global framework to develop algorithms. Silicis is a new formal framework for designing [verification] algorithms.
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  • 2
    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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  • 3
    Simple genetic programming framework. Features a robust set of interfaces and standard implementations for rapid development and ease of experimentation.
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  • 4
    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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  • 5
    A Java framework to create multi-threaded dispatching applications. It is a framework that realizes an application pattern that often appears while creating business applications.
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  • 6
    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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  • 7
    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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  • 8
    Procedural content generation of deterministic and complex entities, with properties and other entities inside, defined by an editable XML file, along with a framework to simulate actions, compositions, and interactions of entities.
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  • 9
    Web-Service for discrete dynamic systems' model description and simulation. Firstly, recursive procedures of stochastic optimization are added. The framework for open and closed loop model description and simulation.
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