Solving Games and All That

Abstract : Efficient best-first search algorithms have been developed for deterministic two-player games with two-outcome.We present a formal framework to represent such best-first search algorithms.The framework is general enough to express popular algorithms such as Proof Number Search, Monte Carlo Tree Search, and the Product Propagation algorithm.We then show how a similar framework can be devised for two more general settings: two-player games with multiple outcomes, and the model checking problem in modal logic K.This gives rise to new Proof Number and Monte Carlo inspired search algorithms for these settings.Similarly, the alpha-beta pruning technique is known to be very important in games with sequential actions.We propose an extension of this technique for stacked-matrix games, a generalization of zero-sum perfect information two-player games that allows simultaneous moves.
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Abdallah Saffidine. Solving Games and All That. Artificial Intelligence [cs.AI]. Université Paris Dauphine - Paris IX, 2013. English. ⟨NNT : 2013PA090069⟩. ⟨tel-01022750⟩

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