Abstract
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.
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© 1998 Springer-Verlag Wien
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Poli, R. (1998). Discovery of Symbolic, Neuro-Symbolic and Neural Networks with Parallel Distributed Genetic Programming. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_92
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DOI: https://doi.org/10.1007/978-3-7091-6492-1_92
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83087-1
Online ISBN: 978-3-7091-6492-1
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