Discovery of Symbolic, Neuro-Symbolic and Neural Networks with Parallel Distributed Genetic Programming
Parallel Distributed Genetic Programming (PDGP) is a new form of genetic programming suitable for the development of parallel programs in which symbolic and neural processing elements can be combined in a free and natural way. This paper describes the representation for programs and the genetic operators on which PDGP is based. Experimental results on the XOR problem axe also reported.
KeywordsGenetic Programming Parallel Program Active Node Genetic Operator Fitness Evaluation
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