Publication Details

Semantically-Oriented Mutation Operator in Cartesian Genetic Programming for Evolutionary Circuit Design

HODAŇ David, MRÁZEK Vojtěch and VAŠÍČEK Zdeněk. Semantically-Oriented Mutation Operator in Cartesian Genetic Programming for Evolutionary Circuit Design. In: GECCO 2020 - Proceedings of the 2020 Genetic and Evolutionary Computation Conference. Cancún: Association for Computing Machinery, 2020, pp. 940-948. ISBN 978-1-4503-7128-5. Available from: http://arxiv.org/abs/2004.11018
Type
conference paper
Language
english
Authors
URL
Keywords

Cartesian genetic programming, semantic operator, semantic mutation, evolutionary circuit design

Abstract

Despite many successful applications, Cartesian Genetic Programming (CGP) suffers from limited scalability, especially when used for evolutionary circuit design. Considering the multiplier design problem, for example, the 5×5-bit multiplier represents the most complex circuit evolved from a randomly generated initial population. The efficiency of CGP highly depends on the performance of the point mutation operator, however, this operator is purely stochastic. This contrasts with the recent developments in Genetic Programming (GP), where advanced informed approaches such as semantic-aware operators are incorporated to improve the search space exploration capability of GP. In this paper, we propose a semantically-oriented mutation operator (SOMO) suitable for the evolutionary design of combinational circuits. SOMO uses semantics to determine the best value for each mutated gene. Compared to the common CGP and its variants as well as the recent versions of Semantic GP, the proposed method converges on common Boolean benchmarks substantially faster while keeping the phenotype size relatively small. The successfully evolved instances presented in this paper include 10-bit parity, 10+10-bit adder and 5×5-bit multiplier. The most complex circuits were evolved in less than one hour with a single-thread implementation running on a common CPU.

Published
2020
Pages
940-948
Proceedings
GECCO 2020 - Proceedings of the 2020 Genetic and Evolutionary Computation Conference
Conference
Genetic and Evolutionary Computations Conference 2020, Cancun, MX
ISBN
978-1-4503-7128-5
Publisher
Association for Computing Machinery
Place
Cancún, MX
DOI
UT WoS
000605292300109
EID Scopus
BibTeX
@INPROCEEDINGS{FITPUB12194,
   author = "David Hoda\v{n} and Vojt\v{e}ch Mr\'{a}zek and Zden\v{e}k Va\v{s}\'{i}\v{c}ek",
   title = "Semantically-Oriented Mutation Operator in Cartesian Genetic Programming for Evolutionary Circuit Design",
   pages = "940--948",
   booktitle = "GECCO 2020 - Proceedings of the 2020 Genetic and Evolutionary Computation Conference",
   year = 2020,
   location = "Canc\'{u}n, MX",
   publisher = "Association for Computing Machinery",
   ISBN = "978-1-4503-7128-5",
   doi = "10.1145/3377930.3390188",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/12194"
}
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