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Ting-Han Wei

2 accepted papers

2024

Expected Work Search: Combining Win Rate and Proof Size Estimation

Owen Randall, Martin Müller, Ting-Han Wei, Ryan Hayward
IJCAI 2024poster

We propose Expected Work Search (EWS), a new game solving algorithm. EWS combines win rate estimation, as used in Monte Carlo Tree Search, with proof size estimation, as used in Proof Number Search. The search efficiency of EWS stems from minimizing a novel notion of Expected Work, which predicts th…

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2024

Monte Carlo Tree Search in the Presence of Transition Uncertainty

Farnaz Kohankhaki, Kiarash Aghakasiri, Hongming Zhang, Ting-Han Wei, Chao Gao, Martin Müller
AAAI 2024technical

Monte Carlo Tree Search (MCTS) is an immensely popular search-based framework used for decision making. It is traditionally applied to domains where a perfect simulation model of the environment is available. We study and improve MCTS in the context where the environment model is given but imperfect…

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