Download PDF by Aske Plaat, Jaap van den Herik, Walter Kosters: Advances in Computer Games: 14th International Conference,

By Aske Plaat, Jaap van den Herik, Walter Kosters

ISBN-10: 3319279912

ISBN-13: 9783319279916

This booklet constitutes the completely refereed post-conference proceedings of the 14th overseas convention on Advances in computing device video games, ACG 2015, held in Leiden, The Netherlands, in July 2015. The 22 revised complete papers provided have been rigorously reviewed and selected from 34 submissions. The papers conceal a variety of topics akin to Monte-Carlo Tree seek and its improvements;  theoretical features and complexity; research of video game features; seek algorithms; and laptop studying.

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Additional 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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81–92. Springer, Heidelberg (2011) 11. : Investigating the limits of Monte-Carlo tree search methods in computer go. , Plaat, A. ) CG 2013. LNCS, vol. 8427, pp. 39–48. Springer, Heidelberg (2014) 12. : Efficiency of static knowledge bias in Monte-Carlo tree search. , Plaat, A. ) CG 2013. LNCS, vol. 8427, pp. 26–38. Springer, Heidelberg (2014) 13. : Fast evolutionary adaptationfor Monte Carlo tree search. M. ) EvoApplications 2014. LNCS, vol. 8602, pp. 349–360. Springer, Heidelberg (2014) 14. : Knowledge-based fast evolutionary MCTS for general video game playing.

We have written EPT programs that play the games of Amazons, Breakthrough, and Havannah and we will refer to them as Amabot, Breakbot, and Havbot. Amabot was originally written using mini-max techniques and, playing under the name Invader, was one of the top Amazons programs at the Computer Olympiads from 2001–2005 [11], but never finished in first place. After converting from mini-max to EPT, Amabot has won each of the last five Computer Olympiads it has entered. Breakbot is a more recent program.

Plaat et al. ): ACG 2015, LNCS 9525, pp. 20–28, 2015. 1007/978-3-319-27992-3 3 Playout Policy Adaptation for Games 21 Later improvements of Cadia Player are N-Grams and the last good reply policy [27]. They have been applied to GGP so as to improve playouts by learning move sequences. A recent development in GGP is to have multiple playout strategies and to choose the one which is the most adapted to the problem at hand [26]. A related domain is the learning of playout policies in single-player problems.

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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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