Research Article
Enhance Performance of Action Evaluation Functions with Stochastic Optimization Algorithms
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@INPROCEEDINGS{10.1007/978-3-319-56357-2_19, author={Nguyen Huy and Dao Nam and Dang Quoc}, title={Enhance Performance of Action Evaluation Functions with Stochastic Optimization Algorithms}, proceedings={Context-Aware Systems and Applications. 5th International Conference, ICCASA 2016, Thu Dau Mot, Vietnam, November 24-25, 2016, Proceedings}, proceedings_a={ICCASA}, year={2017}, month={6}, keywords={}, doi={10.1007/978-3-319-56357-2_19} }- Nguyen Huy
Dao Nam
Dang Quoc
Year: 2017
Enhance Performance of Action Evaluation Functions with Stochastic Optimization Algorithms
ICCASA
Springer
DOI: 10.1007/978-3-319-56357-2_19
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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