By Aske Plaat, Jaap van den Herik, Walter Kosters
This ebook constitutes the completely refereed post-conference proceedings of the 14th foreign convention on Advances in machine video games, ACG 2015, held in Leiden, The Netherlands, in July 2015. The 22 revised complete papers awarded have been rigorously reviewed and selected from 34 submissions. The papers disguise a variety of topics corresponding to Monte-Carlo Tree seek and its improvements; theoretical facets and complexity; research of video game features; seek algorithms; and desktop 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
Hsueh et al. 4. Backpropagation. The result of the playout, also called reward, is updated from terminal state back to all its ancestors in the selected path during selection. Recently, several researchers applied MCTS to CDC. This paper brieﬂy reviews the work in [33, 34]. In , their program DIABLO used non-deterministic nodes, so-called in their article, to contain all inner nodes for all the possible outcomes of the ﬂipping actions. In the rest of this paper, non-deterministic nodes are called chance nodes, since they are conceptually similar.
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.
The three strongest Havannah playing programs all play on Little Golem and, though maybe slightly weaker than the other two, the MCTS version of Havbot plays a very similar game to the other two. Even though the evaluation function for Havbot is still quite primitive the program is making some promising looking moves and is outperforming its MCTS counterpart. As the evaluation continues to improve we feel there is great potential for this program. As a side note, Amabot and Breakbot are now so strong that progress comes very slowly.
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