Probabilistic incremental program evolution: Stochastic search through program space

RafaŁ Satustowicz, Jürgen Schmidhuber

Research output: Chapter in Book/Report/Conference proceedingConference contribution

27 Scopus citations


Probabilistic Incremental Program Evolution (PIPE) is a novel technique for automatic program synthesis. We combine probability vector coding of program instructions [Schmidhuber, 1997], Population- Based Incremental Learning (PBIL) [Baluja and Caruana, 1995] and tree-coding of programs used in variants of Genetic Programming (GP) [Cramer, 1985; Koza, 1992]. PIPE uses a stochastic selection method for successively generating better and better programs according to an adaptive “probabilistic prototype tree”. No crossover operator is used. We compare PIPE to Koza’s GP variant on a function regression problem and the 6-bit parity problem.
Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number of pages8
ISBN (Print)3540628584
StatePublished - Jan 1 1997
Externally publishedYes


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