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—Monte Carlo Tree Search (MCTS) is a recently proposed search method that combines the precision of tree search with the generality of random sampling. It has received considerable interest due to its spectacular success in the difficult problem of computer Go, but has also proved beneficial in a range of other domains. This paper is a survey of the(More)
—Monte Carlo tree search (MCTS) is an AI technique that has been successfully applied to many deterministic games of perfect information. This paper investigates the application of MCTS methods to games with hidden information and uncertainty. In particular, three new information set MCTS (ISMCTS) algorithms are presented which handle different sources of(More)
—In this paper, we examine the use of Monte Carlo Tree Search (MCTS) for a variant of one of the most popular and profitable games in the world: the card game Magic: The Gathering (M:TG). The game tree for M:TG has a range of distinctive features, which we discuss here, and has incomplete information through the opponent's hidden cards, and randomness(More)
—We present a controller for the Physical Travelling Salesman Problem (PTSP), a path planning and steering problem in a simulated continuous real-time domain. Our approach is hierarchical, using domain-specific algorithms and heuristics to plan a coarse-grained route and Monte Carlo Tree Search (MCTS) to plan and steer along fine-grained paths. The MCTS(More)
The transition graph of a cellular automaton (CA) is a graphi-cal representation of the CA's global dynamics. Studying auto-morphisms of transition graphs allows us to identify symmetries in this global dynamics. We conduct a computational study of numbers of automorphisms for the elementary cellular automata (ECAs) on finite lattices. The ECAs are(More)
The transition graph of a cellular automaton (CA) represents the CA's global dynamics. The automorphisms of the transition graph are its self-isomorphisms or " symmetries " , and in a sense these are precisely the symmetries of the CA's dynamics. Previously we have argued that studying how the total number of automorphisms varies with the number of cells on(More)
Monte Carlo Tree Search (MCTS) has produced many recent breakthroughs in game AI research, particularly in computer Go. In this paper we consider how MCTS can be applied to create engaging AI for a popular commercial mobile phone game: Spades by AI Factory , which has been downloaded more than 2.5 million times. In particular, we show how MCTS can be(More)