Tactical Analysis, Board Games AI
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"Large Scale Monte Carlo Tree Search on GPU"
Large Scale Monte Carlo Tree Search on GPU GPU+HK大ávモンテカルロ木探索 Doctoral Dissertation ¿7論£ Kamil Marek Rocki ロツキ カミル >L#ク Submitted to Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo in partial fulfillment of the requirements for the degree of Doctor of Information Science and Technology Thesis Supervisor: Reiji Suda (½田L¯) Professor of Computer Science August, 2011 Abstract: Monte Carlo Tree Search (MCTS) is a method for making optimal decisions in artificial intelligence (AI) problems, typically for move planning in combinatorial games. It combines the generality of random simulation with the precision of tree search. Research interest in MCTS has risen sharply due to its spectacular success with computer Go and its potential application to a number of other difficult problems. Its application extends beyond games, and MCTS can theoretically be applied to any domain that can be described in terms of (state, action) pairs, as well as it can be used to simulate forecast outcomes such as decision support, control, delayed reward problems or complex optimization. The main advantages of the MCTS algorithm consist in the fact that, on one hand, it does not require any strategic or tactical knowledge about the given domain to make reasonable decisions, on the other hand algorithm can be halted at any time to return the current best estimate. So far, current research has shown that the algorithm can be parallelized on multiple CPUs. The motivation behind this work was caused by the emerging GPU- based systems and their high computational potential combined with the relatively low power usage compared to CPUs. -
EXPTIME Hardness of an N by N Custodian Capture Game
algorithms Article EXPTIME Hardness of an n by n Custodian Capture Game Fumitaka Ito 1,†,‡, Masahiko Naito 1,‡, Naoyuki Katabami 1,‡ and Tatsuie Tsukiji 2,* 1 Department of Science and Engineering, Tokyo Denki University, Tokyo 120-8551, Japan; [email protected] (F.I.); [email protected] (M.N.); [email protected] (N.K.) 2 Graduate School of Advanced Science and Technology, Tokyo Denki University, Tokyo 120-8551, Japan * Correspondence: [email protected] † Current address: Oaza Ishizuka, Hikigun Hatoyama-tyou, Saitama 350-0394, Japan. ‡ These authors contributed equally to this work. Abstract: Custodian capture occurs when a player has placed two of his pieces on the opposite sides of an orthogonal line of the opponent’s men. Each piece moves like the rook in Chess. Different cultures played it from pre-modern times in two-player strategy board games, Ludus Latrunculorum (Kowalski’s reconstruction), Hasami shogi in Japan, Mak-yek in Thailand and Myanmar, Ming Mang in Tibet, and so on. We prove that a custodian capture game on n × n square board is EXPTIME hard if the first player to capture five or more men in total wins. Keywords: computational complexity; custodial capture; EXPTIME hard; generalized game; repetition 1. Introduction Custodial capture occurs on a square lattice board when a player has placed two of his pieces on the opposite sides of an orthogonal line of the opponent’s men. Different cultures played it in two-player strategy (i.e., perfect information) board games [1,2]. In A History Citation: Ito, F.; Naito, M.; Katabami, of Chess [3], after introducing Tafl games in Nordic and Celtic, Murray noted that “the N.; Tsukiji, T. -
Algorithmic Approaches for Playing and Solving Shannon Games
Algorithmic Approaches for Playing and Solving Shannon Games Rune Rasmussen Bachelor of Information Technology in Software Engineering Queensland University of Technology A thesis submitted to the Faculty of Information Technology at the Queensland University of Technology in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Principal Supervisor: Dr Frederic Maire Associate Supervisor: Dr Ross Hayward Faculty of Information Technology Queensland University of Technology Brisbane, Queensland, 4000, AUSTRALIA 2007 STATEMENT OF OWNERSHIP The work contained in this thesis has not been previously submitted to meet requirements for an award at this or any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made. Signature: Rune Rasmussen Date: ii iii ACKNOWLEDGEMENTS I would like to thank my supervisors Frederic Maire and Ross Hayward, who have been patient and helpful in providing this most valuable learning experience. In addition, I thank my wife Kerry and my children for their patience and trust in me, as I left a trade career as an Electrician to pursue and finish this journey for a more interesting career path and hopefully a more prosperous life. iv v ABSTRACT The game of Hex is a board game that belongs to the family of Shannon games, which are connection-oriented games where players must secure certain connected components in graphs. The problem of solving Hex is a decision problem com- plete in PSPACE, which implies that the problem is NP-Hard. Although the Hex problem is difficult to solve, there are a number of problem reduction methods that allow solutions to be found for small Hex boards within practical search limits. -
Backgammon Is Hard
Backgammon is Hard R. Teal Witter1[0000−0003−3096−3767] NYU Tandon, Brooklyn NY 11201, USA [email protected] Abstract. We study the computational complexity of the popular board game backgammon. We show that deciding whether a player can win from a given board configuration is NP-Hard, PSPACE-Hard, and EXPTIME- Hard under different settings of known and unknown opponents' strate- gies and dice rolls. Our work answers an open question posed by Erik Demaine in 2001. In particular, for the real life setting where the oppo- nent's strategy and dice rolls are unknown, we prove that determining whether a player can win is EXPTIME-Hard. Interestingly, it is not clear what complexity class strictly contains each problem we consider because backgammon games can theoretically continue indefinitely as a result of the capture rule. Keywords: Computational complexity · Backgammon 1 Introduction Backgammon is a popular board game played by two players. Each player has 15 pieces that lie on 24 points evenly spaced on a board. The pieces move in opposing directions according to the rolls of two dice. A player wins if they are the first to move all of their pieces to their home and then off the board. The quantitative study of backgammon began in the early 1970's and algo- rithms for the game progressed quickly. By 1979, a computer program had beat the World Backgammon Champion 7 to 1 [2]. This event marked the first time a computer program bested a reigning human player in a recognized intellec- tual activity. Since then, advances in backgammon programs continue especially through the use of neural networks [11,17,18].