Abstract
In this paper, we describe how to optimize the weights of board cells from data set of game records, the weights of board cells are applied in the action evaluation function which usually uses to enhance Monte Carlo Tree Search programs. The general optimization process is introduced and discussed, and one specific method is implemented. We use Othello as a testing environment, and experiment results is better if the action evaluation function is better.
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Huy, N.Q., Nam, D.D., Quoc, D.C. (2017). Enhance Performance of Action Evaluation Functions with Stochastic Optimization Algorithms. In: Cong Vinh, P., Tuan Anh, L., Loan, N., Vongdoiwang Siricharoen, W. (eds) Context-Aware Systems and Applications. ICCASA 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 193. Springer, Cham. https://doi.org/10.1007/978-3-319-56357-2_19
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DOI: https://doi.org/10.1007/978-3-319-56357-2_19
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