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You can try using an "Open-Loop" MCTS approach, instead of the standard "closed-loop" one, and eliminate chance nodes altogether. See, for example, Open Loop Search for General Video Game Playing. In a "standard" (closed-loop) implementation, you would store a game state in every normal (non-chance) node. Whenever there is a chance event, you would ...


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It is very likely that you want an algorithm like Counterfactual Minimax Regret. This algorithm has several variants, but they differ mostly in their efficiency. CFR is the algorithm that was used to solve 2-Player Poker, although the solution comes from one of its more advanced versions. The algorithm is highly applicable to other games of incomplete ...


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That really depends on the nature of the problem. I will assume that you asked this question on the AI stackexchange because you thought that there was a type of AI that would solve the problem. By giving a certain chance that something happens, you also imply that if the number of samples increases, the relative frequency of an outcome will converge to the ...


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