Download e-book for iPad: Advances in Computer Games: 14th International Conference, by Aske Plaat, Jaap van den Herik, Walter Kosters

By Aske Plaat, Jaap van den Herik, Walter Kosters

ISBN-10: 3319279912

ISBN-13: 9783319279916

ISBN-10: 3319279920

ISBN-13: 9783319279923

This e-book constitutes the completely refereed post-conference complaints of the 14th foreign convention on Advances in machine video games, ACG 2015, held in Leiden, The Netherlands, in July 2015.

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Read Online or Download Advances in Computer Games: 14th International Conference, ACG 2015, Leiden, The Netherlands, July 1-3, 2015, Revised Selected Papers PDF

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Extra info for Advances in Computer Games: 14th International Conference, ACG 2015, Leiden, The Netherlands, July 1-3, 2015, Revised Selected Papers

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Cazenave Algorithm 4. playouts[m] + c × log(t) value ← w p p if value > bestV alue then bestV alue ← value bestM ove ← m end if end for play (board, bestM ove) player ← opponent (player) res ← UCT (board, player, policy) update t with res else t ← new entry of board in the transposition table res ← playout (board, player, policy) update t with res end if return res – – – – has been solved up to size 6 × 5 using Job Level Proof Number Search [25]. The best program for Breakthrough 8 × 8 uses MCTS combined with an evaluation function after a short playout [19].

70 %. 1 Introduction Chinese dark chess (CDC), widely played in Chinese community, is a two-player game and also a partially observable (PO) game with symmetric hidden information. The set of pieces in CDC is the same as those in Chinese chess; however, the pieces are faced down initially so both players do not know what the pieces are, until they are flipped. In [8], the state space complexity of the game was estimated to be 1037 between those of Draughts and chess, while the game-tree complexity was estimated to be 10135 between those of chess and Chinese chess without considering chance nodes.

References 1. : A survey of monte carlo tree search methods. IEEE Trans. Comput. Intell. AI Games 4(1), 1–49 (2012) 2. : Efficient selectivity and backup operators in monte-carlo tree search. In: 5th International Conference on Computers and Games, CG 2006, Turin, Italy, pp. 72–84 (2006) 3. : Combining online and offline knowledge in UCT. In: Ghahramani, Z. ) Proceedings of the 24th International Conference on Machine Learning (ICML 2007), pp. 273–280. ACM, New York (2007) 4. : Progressive strategies for monte-carlo tree search.

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Advances in Computer Games: 14th International Conference, ACG 2015, Leiden, The Netherlands, July 1-3, 2015, Revised Selected Papers by Aske Plaat, Jaap van den Herik, Walter Kosters


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