Abstract
Genetic Programming is a method of program discovery
consisting of a special kind of genetic algorithm
capable of operating on non-linear chromosomes (parse
trees) representing programs and an interpreter which
can run the programs being optimised. This paper
describes PDGP (Parallel Distributed Genetic
Programming), a new form of genetic programming which
is suitable for the development of fine-grained
parallel programs. PDGP is based on a graph-like
representation for parallel programs which is
manipulated by crossover and mutation operators which
guarantee the syntactic correctness of the offspring.
The paper describes these operators and reports some
preliminary results obtained with this paradigm.
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