Evolving parsimonious circuits through Shapley value-based genetic programming

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Evolutionary analog circuit design is a challenging task due to the large search space incurred by the circuit topology and device values. Applying genetic operators on randomly selected genes may make it difficult to identify which part of sub-circuit is beneficial to the evolution and even destroy useful sub-circuits, potentially incurring stagnation of the evolutionary process and bloat on the evolved circuits. In this paper, we propose a tree-based approach called Shapley Circuit Tree that incorporates Shapley values for quantifying the contribution of each function node of the circuit tree to the performance of the whole tree, to guide the evolutionary process. Our experiments on three benchmarks show that the proposed approach is able to evolve analog circuits with smaller area while converging faster than existing approaches.
Original languageEnglish
Title of host publicationGECCO '22
Subtitle of host publicationProceedings of the Genetic and Evolutionary Computation Conference Companion
EditorsJonathan E. Fieldsend
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Number of pages4
ISBN (Electronic)9781450392686
Publication statusPublished - 19 Jul 2022
EventGECCO '22: Genetic and Evolutionary Computation Conference - Boston, United States
Duration: 9 Jul 202213 Jul 2022

Publication series

NameGECCO: Genetic and Evolutionary Computation Conference


ConferenceGECCO '22: Genetic and Evolutionary Computation Conference
Abbreviated titleGECCO 2022
Country/TerritoryUnited States

Bibliographical note

Funding Information:
This work was support by the Research Institute of Trustworthy Autonomous Systems (RITAS), the Guangdong Provincial Key Laboratory (Grant No. 2020B121201001), the Program for Guangdong Introducing Innovative and Enterpreneurial Teams (Grant No. 2017ZT07X386), the Shenzhen Science and Technology Program (Grant No. KQTD2016112514355531).

Publisher Copyright:
© 2022 Owner/Author.


  • evolutionary analog circuit design
  • evolvable hardware
  • genetic programming
  • shapley value
  • tree-based circuit representation

ASJC Scopus subject areas

  • Software
  • Computational Mathematics
  • Artificial Intelligence
  • Theoretical Computer Science


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