This paper addresses the broader topic of using game theoretical learning mechanisms to efficiently and effectively identify relevant (e.g., optimal and non-mixed) solutions to large scale optimization problems. The longer-term goal is for the proposed MCFP-variants to become established methods for finding pure Nash equilibria and global optima of large-scale problems.
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Kiatsupaibul et al. (2024) studied this question.
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