Evolving EFSMs solving a path-planning problem by genetic programming

Maxim Buzdalov; Andriy Sokolov

doi:10.1145/2330784.2330880

Evolving EFSMs solving a path-planning problem by genetic programming

Maxim Buzdalov, Andriy Sokolov

ITMO University

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

1 Citation (Scopus)

Abstract

In this paper, we present an approach to evolving of an algorithm encoded as an extended finite-state machine that solves a simple path-planning problem - finding a path in an unknown area filled with obstacles using a constant amount of memory - by means of genetic programming. Experiments show that in 100% of cases a reasonably correct EFSM with behavior similar to one of the BUG algorithms is evolved.

Original language	English
Title of host publication	GECCO '12
Subtitle of host publication	Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Editors	Terence Soule
Publisher	Association for Computing Machinery
Pages	591-594
Number of pages	4
ISBN (Electronic)	978-1-4503-1178-6
DOIs	https://doi.org/10.1145/2330784.2330880
Publication status	Published - 07 Jul 2012
Externally published	Yes
Event	GECCO 2012 - Genetic and Evolutionary Computation Conference - Philadelphia, United States of America Duration: 07 Jul 2012 → 11 Jul 2012

Conference

Conference	GECCO 2012 - Genetic and Evolutionary Computation Conference
Country/Territory	United States of America
City	Philadelphia
Period	07 Jul 2012 → 11 Jul 2012

Keywords

bug algoritms
finite-state machine
genetic programming
path-planning problem

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10.1145/2330784.2330880

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title = "Evolving EFSMs solving a path-planning problem by genetic programming",

abstract = "In this paper, we present an approach to evolving of an algorithm encoded as an extended finite-state machine that solves a simple path-planning problem - finding a path in an unknown area filled with obstacles using a constant amount of memory - by means of genetic programming. Experiments show that in 100% of cases a reasonably correct EFSM with behavior similar to one of the BUG algorithms is evolved.",

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booktitle = "GECCO '12",

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Buzdalov, M & Sokolov, A 2012, Evolving EFSMs solving a path-planning problem by genetic programming. in T Soule (ed.), GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation. Association for Computing Machinery, pp. 591-594, GECCO 2012 - Genetic and Evolutionary Computation Conference, Philadelphia, Pennsylvania, United States of America, 07 Jul 2012. https://doi.org/10.1145/2330784.2330880

Evolving EFSMs solving a path-planning problem by genetic programming. / Buzdalov, Maxim; Sokolov, Andriy.
GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation. ed. / Terence Soule. Association for Computing Machinery, 2012. p. 591-594.

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

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KW - finite-state machine

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Evolving EFSMs solving a path-planning problem by genetic programming

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