A framework for domain-specific, hyper-heuristic evolution
HH-Evolver is a framework for domain-specific, hyper-heuristic evolution.
HH-Evolver automates the design of domain-specific heuristics for planning domains. Hyper-heuristics generated by our tool can then be used with combinatorial search algorithms such as A* and IDA* for solving problems of the given domain.
An implementation of the 'Provider' pattern for .NET 1.1 framework, plug in installation support, and generic entity model base classes capable of binding to a user interface.
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.
GEP is an evolutionary algorithm for function finding. This framework is a powerful way of expressing and coding genetic-like structures and quickly finding solutions through evolution by common genetic operators.
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CuberGA project is the flexible Genetic Algorithms framework. Realize your ideas easy with deliveries of this project. Keywords: genetic algorithms, framework, permutation, mutation, crossover, genotype, selection, survival, Левченко Илья.
LispSharp is a fully compiled lisp implementation for the .NETFramework.
It uses a Lisp dialect similar to ISO Lisp, it has a Command-line toplevel
compiler with Read Compile Print Loop.It references any .NET DLL and produces standard .NET assembly.
GraphSmart is a collection of graph data structures and algorithms utilizing generics and the Microsoft .NET 2.0 Framework. Included items are commonly used in software engineering but not included in the .NET 2.0 Framework class library.
ScienceNET is a open source library written in C# which aims to provide a self contained clean .NETframework for neural networks, genetic algorithms, optimization, image processing and for other domains of a computational science.