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HODAŇ, D. MRÁZEK, V. VAŠÍČEK, Z.
Original Title
Semantically-oriented mutation operator in cartesian genetic programming for evolutionary circuit design
Type
journal article in Web of Science
Language
English
Original Abstract
Cartesian genetic programming (CGP) represents the most efficient method for the evolution of digital circuits. Despite many successful applications, however, CGP suffers from limited scalability, especially when used for evolutionary circuit design, i.e. design of circuits from a randomly initialized population. Considering the multiplier design problem, for example, the 5×5-bit multiplier represents the most complex circuit designed by the evolution from scratch. 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 (SOMOk) suitable for the evolutionary design of combinational circuits. In contrast to standard point mutation modifying the values of the mutated genes randomly, the proposed operator uses semantics to determine the best value for each mutated gene. Compared to the common CGP and its variants, 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
1. 12. 2021
ISBN
1389-2576
Periodical
Genetic Programming and Evolvable Machines
Year of study
22
Number
4
State
United States of America
Pages from
539
Pages to
572
Pages count
34
URL
https://link.springer.com/article/10.1007%2Fs10710-021-09416-6
BibTex
@article{BUT175819, author="David {Hodaň} and Vojtěch {Mrázek} and Zdeněk {Vašíček}", title="Semantically-oriented mutation operator in cartesian genetic programming for evolutionary circuit design", journal="Genetic Programming and Evolvable Machines", year="2021", volume="22", number="4", pages="539--572", doi="10.1007/s10710-021-09416-6", issn="1389-2576", url="https://link.springer.com/article/10.1007%2Fs10710-021-09416-6" }