Application of Monte Carlo Tree Optimization Algorithm on Hex Chess

Hex Chess attracts more and more people because of the simple rules, but also because of the simple rules, it brings complex algorithms. The simple Monte Carlo tree search process is often very slow due to the large amount of computation. In the double game, the Monte Carlo algorithm cannot converge to the best decision strategy of the double game. This paper proposes an improved algorithm of Monte Carlo tree search combined with MTD(f) algorithm, so that the search results are not distorted by the randomness of Monte Carlo algorithm. In order to further improve the computational efficiency of the search algorithm in the two-player game, the TCL and the connected domain strategy are adopted. Compared with the improved algorithm, not only shortens the time of Monte Carlo tree search, but also improves the performance.

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