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Evolving parsimonious circuits through shapley value-based genetic programming

Published: 19 July 2022 Publication History

Abstract

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.

References

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Federico Castejón and Enrique J Carmona. 2018. Automatic design of analog electronic circuits using grammatical evolution. Appl. Soft Comput. 62 (2018), 1003--1018.
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Amirata Ghorbani and James Zou. 2020. Neuron shapley: Discovering the responsible neurons. arXiv preprint arXiv:2002.09815 (2020).
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John R Koza, David Andre, Martin A Keane, and Forrest H Bennett III. 1999. Genetic programming III: Darwinian invention and problem solving. Vol. 3. Morgan Kaufmann.
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John R. Koza, Forrest H Bennett, David Andre, Martin A. Keane, and Frank Dunlap. 1997. Automated synthesis of analog electrical circuits by means of genetic programming. IEEE Trans. Evol. Comput. 1, 2 (1997), 109--128.
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Bo Liu, Yan Wang, Zhiping Yu, Leibo Liu, Miao Li, Zheng Wang, Jing Lu, and Francisco V Fernández. 2009. Analog circuit optimization system based on hybrid evolutionary algorithms. Integration 42, 2 (2009), 137--148.
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Claudio Mattiussi and Dario Floreano. 2007. Analog genetic encoding for the evolution of circuits and networks. IEEE Trans. Evol. Comput. 11, 5 (2007), 596--607.
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Alvin E Roth. 1988. The Shapley value: essays in honor of Lloyd S. Shapley. Cambridge University Press.
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Lloyd S Shapley. 2016. A value for n-person games. Princeton University Press.
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Xinming Shi, Leandro L. Minku, and Xin Yao. 2022. A Novel Tree-based Representation for Evolving Analog Circuits and Its Application to Memristor-Based Pulse Generation Circuit. Under review by Genetic Programming and Evolvable Machines (2022).

Cited By

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  • (2024)Accelerating surrogate assisted evolutionary algorithms for expensive multi-objective optimization via explainable machine learningSwarm and Evolutionary Computation10.1016/j.swevo.2024.10161088(101610)Online publication date: Jul-2024
  • (2024)Tree-Based Genetic Programming for Evolutionary Analog Circuit with Approximate Shapley ValueArtificial Intelligence XLI10.1007/978-3-031-77915-2_18(253-267)Online publication date: 29-Nov-2024

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    Published In

    cover image ACM Conferences
    GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion
    July 2022
    2395 pages
    ISBN:9781450392686
    DOI:10.1145/3520304
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 19 July 2022

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    Author Tags

    1. evolutionary analog circuit design
    2. evolvable hardware
    3. genetic programming
    4. shapley value
    5. tree-based circuit representation

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    Funding Sources

    • Guangdong Provincial Key Laboratory
    • Shenzhen Science and Technology Program
    • Program for Guang- dong Introducing Innovative and Enterpreneurial Teams

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    GECCO '22
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    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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    View all
    • (2024)Accelerating surrogate assisted evolutionary algorithms for expensive multi-objective optimization via explainable machine learningSwarm and Evolutionary Computation10.1016/j.swevo.2024.10161088(101610)Online publication date: Jul-2024
    • (2024)Tree-Based Genetic Programming for Evolutionary Analog Circuit with Approximate Shapley ValueArtificial Intelligence XLI10.1007/978-3-031-77915-2_18(253-267)Online publication date: 29-Nov-2024

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