Evolving efficient list search algorithms

Kfir Wolfson, Moshe Sipper

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


We peruse the idea of algorithmic design through Darwinian evolution, focusing on the problem of evolving list search algorithms. Specifically, we employ genetic programming (GP) to evolve iterative algorithms for searching for a given key in an array of integers. Our judicious design of an evolutionary language renders the evolution of linear-time search algorithms easy. We then turn to the far more difficult problem of logarithmic-time search, and show that our evolutionary system successfully handles this case. Subsequently, because our setup might be perceived as being geared towards the emergence of binary search, we generalize our genomic representation, allowing evolution to assemble its own useful functions via the mechanism of automatically defined functions (ADFs). We show that our approach routinely and repeatedly evolves general and correct efficient algorithms.

Original languageEnglish
Title of host publicationArtificial Evolution - 9th International Conference Evolution Artificielle, EA 2009, Revised Selected Papers
Number of pages12
StatePublished - 23 Jul 2010
Event9th International Conference on Artificial Evolution, EA 2009 - Strasbourg, France
Duration: 26 Oct 200928 Oct 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5975 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference9th International Conference on Artificial Evolution, EA 2009


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