Learn More
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)
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; it has incomplete information through the opponent's hidden cards and randomness through(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)
This paper presents a number of approaches for solving a real-time game consisting of a ship that must visit a number of waypoints scattered around a 2-D maze full of obstacles. The game, the Physical Traveling Salesman Problem (PTSP), which featured in two IEEE conference competitions during 2012, provides a good balance between long-term planning (finding(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)
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)
Monte-Carlo Tree Search (MCTS) is a class of game tree search algorithms that have recently proven successful for deterministic games of perfect information, particularly the game of Go. Determinization is an AI technique for making decisions in stochastic games of imperfect information by analysing several instances of the equivalent deterministic game of(More)
Determinization is a technique for making decisions in games with stochasticity and/or imperfect information by sampling instances of the equivalent deterministic game of perfect information. Monte-Carlo Tree Search (MCTS) is an AI technique that has recently proved successful in the domain of deterministic games of perfect information. This paper studies(More)