ICGA Journal - Volume 32, issue 4

Article Type: Other

DOI: 10.3233/ICG-2009-32401

Citation: ICGA Journal, vol. 32, no. 4, pp. 185-186, 2009

Authors: Erdmann, Jakob

Article Type: Research Article

Abstract: The distinction between games of chance and games of skill is not well-defined at present. We introduce the concept of chanciness for non-deterministic two-player zero-sum games with sequential moves and perfect information. Chanciness quantifies how strongly a game is influenced by chance events. We demonstrate that the relative influence of chance on game outcomes varies with the skill of the playing agents. Therefore, we assign a chanciness value to the combination of a game and a specific set of players. The effective computability of chanciness is demonstrated for exemplary games.

DOI: 10.3233/ICG-2009-32402

Citation: ICGA Journal, vol. 32, no. 4, pp. 187-205, 2009

Authors: Šolak, Rade | Vučković, Vladan

Article Type: Research Article

Abstract: During a chess game, there are two important resources that each player possesses. One is material i.e., the pieces that are at his3 disposal. The other is the time shown on the clock. Until now, efforts that have been invested in the development of chess programs were mostly directed towards evaluation functions and algorithms for searching the state space, while time management did not receive much attention. In this article we consider six models for time management. We experimented with them and succeeded in improving the performance of such sophisticated programs as RYBKA and SHREDDER .

DOI: 10.3233/ICG-2009-32403

Citation: ICGA Journal, vol. 32, no. 4, pp. 206-220, 2009

Authors: Drake, Peter

Article Type: Research Article

Abstract: The dominant paradigm for computer-Go players is Monte-Carlo Tree Search (MCTS). This algorithm builds a search tree by playing many simulated games (playouts ). Each playout consists of a sequence of moves within the tree followed by many moves beyond the tree. Moves beyond the tree are generated by a biased random sampling policy . This note presents a dynamic sampling policy that takes advantage of information from previous playouts. The policy makes moves that, in previous playouts, have been successful replies to immediately preceding moves. Experimental results show that the policy provides a large improvement in playing strength.

DOI: 10.3233/ICG-2009-32404

Citation: ICGA Journal, vol. 32, no. 4, pp. 221-227, 2009

Authors: Haworth, G.McC.

Article Type: Research Article

DOI: 10.3233/ICG-2009-32405

Citation: ICGA Journal, vol. 32, no. 4, pp. 228-228, 2009

Article Type: Other

DOI: 10.3233/ICG-2009-32406

Citation: ICGA Journal, vol. 32, no. 4, pp. 229-229, 2009

Authors: Lin, Ping-Hung | Wu, I-Chen

Article Type: Other

DOI: 10.3233/ICG-2009-32407

Citation: ICGA Journal, vol. 32, no. 4, pp. 230-232, 2009

Authors: Jug, Sven | Schadd, Maarten

Article Type: Other

DOI: 10.3233/ICG-2009-32408

Citation: ICGA Journal, vol. 32, no. 4, pp. 233-234, 2009

Authors: Yen, Shi-Jim | Chou, Cheng-Wei | Kato, Hideki

Article Type: Other

DOI: 10.3233/ICG-2009-32409

Citation: ICGA Journal, vol. 32, no. 4, pp. 235-236, 2009

Authors: Yen, Shi-Jim | Muramatsu, Masakazu | Ito, Takeshi

Article Type: Other

DOI: 10.3233/ICG-2009-32410

Citation: ICGA Journal, vol. 32, no. 4, pp. 237-240, 2009