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 foreign convention on Advances in desktop video games, ACG 2015, held in Leiden, The Netherlands, in July 2015. The 22 revised complete papers provided have been conscientiously reviewed and selected from 34 submissions. The papers hide a variety of topics equivalent to Monte-Carlo Tree seek and its improvements;  theoretical points and complexity; research of video game features; seek algorithms; and laptop studying.

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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

Sample text

In the case of Amabot, we were ultimately able to achieve a win rate of 80 % using EPT over the mini-max based program. We then went on to win the next five Computer Olympiads using EPT. We believe Kloetzer’s program had the potential for similar results, but he did not have the luxury of a pre-existing, strong evaluation function, leaving him at a disadvantage. In 2009, motivated in part by the “Havannah Challenge” [12], a number of projects began to develop an Havannah playing program, including our Havbot project.

5131, pp. 13–24. Springer, Heidelberg (2008) 7. : Programming breakthrough. , Plaat, A. ) CG 2013. LNCS, vol. 8427, pp. 49–59. Springer, Heidelberg (2013) 8. : Experiments with monte-carlo tree search in the game of havannah. ICGA J. 34(3), 140–150 (2011) 9. : Evaluation function based monte-carlo LOA. , Spronck, P. ) ACG 2009. LNCS, vol. 6048, pp. 33–44. Springer, Heidelberg (2010) 10. jsp 11. id=249 12. Havannah#The Havannah Challenge. fr Abstract. Monte-Carlo Tree Search (MCTS) is the state of the art algorithm for General Game Playing (GGP).

De nouvelles heuristiques de recherche appliqu´ees ` a la r´esolution d’Atarigo. In: Intelligence artificielle et jeux, pp. 127–141. Hermes Science (2006) 2. : A survey of Monte Carlo tree search methods. IEEE Trans. Comput. Intell. AI Games 4(1), 1–43 (2012) 3. : Nested Monte-Carlo search. In: Boutilier, C. ) IJCAI, pp. 456– 461 (2009) 4. : Sequential halving applied to trees. IEEE Trans. Comput. Intell. AI Games 7(1), 102–105 (2015) 5. : Discounting and pruning for nested playouts in general game playing.

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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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