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Combining Monte-Carlo Tree Search with Proof-Number Search

Artificial Intelligence 2022-06-09 v1

Abstract

Proof-Number Search (PNS) and Monte-Carlo Tree Search (MCTS) have been successfully applied for decision making in a range of games. This paper proposes a new approach called PN-MCTS that combines these two tree-search methods by incorporating the concept of proof and disproof numbers into the UCT formula of MCTS. Experimental results demonstrate that PN-MCTS outperforms basic MCTS in several games including Lines of Action, MiniShogi, Knightthrough, and Awari, achieving win rates up to 94.0%.

Keywords

Cite

@article{arxiv.2206.03965,
  title  = {Combining Monte-Carlo Tree Search with Proof-Number Search},
  author = {Elliot Doe and Mark H. M. Winands and Dennis J. N. J. Soemers and Cameron Browne},
  journal= {arXiv preprint arXiv:2206.03965},
  year   = {2022}
}

Comments

Accepted at IEEE CoG 2022. Copyright of final version held by IEEE

R2 v1 2026-06-24T11:43:46.637Z