Search Results for "artificial 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.

Library for creation of artificial neural networks in C#. Library supports Hopfield nets, Kohonen nets, feedforward networks, several learning techniques (differential evolution, back propagation, quick propagation, resilient propagation etc.)

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.