By Aske Plaat, Jaap van den Herik, Walter Kosters

This ebook constitutes the completely refereed post-conference lawsuits of the 14th overseas convention on Advances in computing device video games, ACG 2015, held in Leiden, The Netherlands, in July 2015.

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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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Havbot was also a moderately strong MCTS program, but is only slightly stronger using EPT. Like Breakbot, Havbot also plays under the name Wanderer. It has played in a number of Computer Olympiads and also plays on the Little Golem Web site. Though creating an EPT program is straightforward, we will explain in detail (1) the requirements and difficulties of producing a strong EPT program from the perspective of our success with Amabot and Breakbot and (2) our difficulties with Havbot. 2 History We begin with a brief history of our research into MCTS-EPT.

LNCS, vol. 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).

Amazons positions can have more than 2000 legal moves. When building the EPT tree, we evaluate all possible children of a node and only put the top 750 in the tree and then from these we proceed with the usual progressive widening. With Havbot and Breakbot we use the evaluation function to initialize win values in new nodes. Considerable tuning is necessary to find good initial values because, as is so common with MCTS related algorithms, we must find the proper balance so that the tree grows without inappropriate bias.

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