Evolution of Graph-Like Programs with Parallel Distributed Genetic Programming

Parallel Distributed Genetic Programming (PDGP) is a new form of Genetic Programming (GP) suitable for the development of programs with a high degree of parallelism. Programs are represented in PDGP as graphs with nodes representing functions and terminals, and links representing the flow of control and results. The paper presents the representations, the operators and the interpreters used in PDGP, and describes experiments in which PDGP has been compared to standard GP.

• Type: Conference
• Year: 1997
• Where: ICGA
• Authors: Riccardo Poli
• Keywords: Genetic Programming, ICGA 1997, Interpreters, Nodes Representing Functions, Optimization