Publication detail

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

HODAŇ, D. MRÁZEK, V. VAŠÍČEK, Z.

Original Title

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

Type

conference paper

Language

English

Original 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.

Keywords

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

Authors

HODAŇ, D.; MRÁZEK, V.; VAŠÍČEK, Z.

Released

25. 6. 2020

Publisher

Association for Computing Machinery

Location

Cancún

ISBN

978-1-4503-7128-5

Book

GECCO 2020 - Proceedings of the 2020 Genetic and Evolutionary Computation Conference

Pages from

940

Pages to

948

Pages count

9

URL

http://arxiv.org/abs/2004.11018

BibTex

@inproceedings{BUT168122,
  author="David {Hodaň} and Vojtěch {Mrázek} and Zdeněk {Vašíček}",
  title="Semantically-Oriented Mutation Operator in Cartesian Genetic Programming for Evolutionary Circuit Design",
  booktitle="GECCO 2020 - Proceedings of the 2020 Genetic and Evolutionary Computation Conference",
  year="2020",
  pages="940--948",
  publisher="Association for Computing Machinery",
  address="Cancún",
  doi="10.1145/3377930.3390188",
  isbn="978-1-4503-7128-5",
  url="http://arxiv.org/abs/2004.11018"
}