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Computer Science > Artificial Intelligence

arXiv:2206.03965 (cs)
[Submitted on 8 Jun 2022]

Title:Combining Monte-Carlo Tree Search with Proof-Number Search

Authors:Elliot Doe, Mark H. M. Winands, Dennis J. N. J. Soemers, Cameron Browne
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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%.
Comments: Accepted at IEEE CoG 2022. Copyright of final version held by IEEE
Subjects: Artificial Intelligence (cs.AI)
Cite as: arXiv:2206.03965 [cs.AI]
  (or arXiv:2206.03965v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2206.03965

Submission history

From: Dennis Soemers [view email]
[v1] Wed, 8 Jun 2022 15:28:42 UTC (503 KB)
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