Semantically-oriented mutation operator in cartesian genetic programming for evolutionary circuit design
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F21%3APU142942" target="_blank" >RIV/00216305:26230/21:PU142942 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007%2Fs10710-021-09416-6" target="_blank" >https://link.springer.com/article/10.1007%2Fs10710-021-09416-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10710-021-09416-6" target="_blank" >10.1007/s10710-021-09416-6</a>
Alternative languages
Result language
angličtina
Original language name
Semantically-oriented mutation operator in cartesian genetic programming for evolutionary circuit design
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA19-10137S" target="_blank" >GA19-10137S: Designing and exploiting libraries of approximate circuits</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Genetic Programming and Evolvable Machines
ISSN
1389-2576
e-ISSN
1573-7632
Volume of the periodical
22
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
34
Pages from-to
539-572
UT code for WoS article
000702806100001
EID of the result in the Scopus database
2-s2.0-85116194943