Abstract
The automated design of analog circuits presents a significant challenge due to the complexity of circuit topology and parameter selection. Traditional evolutionary algorithms, such as Genetic Programming (GP), have shown potential in this domain but are often hindered by inefficient search processes and the large design space. Furthermore, fitness evaluation in the evolutionary design of circuits is often computationally very expensive. In this paper, we introduce a novel evolutionary framework that leverages approximate Shapley values to guide the optimization process in tree-based genetic programming for analog circuit design. Our approach addresses the computational challenges associated with computing Shapley values by introducing a two-stage evolutionary framework that includes a Shapley Value Library (SVlib) and a KNNbased prediction for efficient estimation of Shapley values. Our proposed work not only enhances the search efficiency by focusing on the most beneficial subcircuits but also leads to more compact and efficient circuit designs. Furthermore, fitness evaluation in the evolutionary design of circuits is often computationally very expensive experiments, we verify that our framework accelerates evolutionary convergence and outperforms traditional methods in terms of circuit optimization.
Original language | English |
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Title of host publication | Forty-fourth SGAI International Conference on Artificial Intelligence |
Publication status | Accepted/In press - 30 Aug 2024 |
Event | Forty-fourth SGAI International Conference on Artificial Intelligence - Cambridge, United Kingdom Duration: 17 Dec 2024 → 19 Dec 2024 Conference number: 44 http://bcs-sgai.org/ai2024/ |
Publication series
Name | Lecture Notes in Artificial Intelligence |
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Publisher | Springer |
ISSN (Print) | 2945-9133 |
ISSN (Electronic) | 2945-9141 |
Conference
Conference | Forty-fourth SGAI International Conference on Artificial Intelligence |
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Abbreviated title | AI-2024 |
Country/Territory | United Kingdom |
City | Cambridge |
Period | 17/12/24 → 19/12/24 |
Internet address |