- author = "Riccardo Poli",
- title = "Discovery of Symbolic, Neuro-Symbolic and Neural Networks with Parallel Distributed Genetic Programming",
- booktitle = "Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference, ICANNGA97",
- year = "1997",
- editor = "George D. Smith and Nigel C. Steele and Rudolf F. Albrecht",
- pages = "419--423",
- address = "University of East Anglia, Norwich, UK",
- publisher = "Springer-Verlag",
- note = "published in 1998",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "3-211-83087-1",
-
URL = "
http://cswww.essex.ac.uk/staff/rpoli/papers/Poli-ICANNGA1997.pdf",
-
URL = "
http://citeseer.ist.psu.edu/330920.html",
-
DOI = "
doi:10.1007/978-3-7091-6492-1_92",
- size = "4 pages",
- 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 are also reported.",
-
notes = "see also \cite{poli:1996:sn-snnTR}
http://www.sys.uea.ac.uk/Research/ResGroups/MAG/ICANNGA97/papers_frame.html
Here PDGP was applied to the XOR problem with the only objective of exploring the possibilities offered by this representation. No comparison with GP was made. Weights were added to the links between nodes, to allow the evolution of all sorts of things (logic networks, neural nets, neuro-algebraic nets, etc.). Efforts with logic nets were in the region of 2,000-3,000",
