By Aske Plaat, Jaap van den Herik, Walter Kosters
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 rigorously reviewed and selected from 34 submissions. The papers disguise a variety of topics resembling Monte-Carlo Tree seek and its improvements; theoretical elements and complexity; research of online game features; seek algorithms; and computing device 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
Future work includes optimizing the performance of adaptive playouts. The experiments showed that parallel MCTS is harmed by a global lock on the adaptive weights. Removing this bottleneck will lead to a direct increase in playing strength and allows scaling to more than 16 threads. Additionally, the playout policies need informative features to learn useful moves. The experiments showed that simple and fast features can adapt to quite complex cases. Nevertheless, it is an open question which features are best suited to improve adaptive playouts.
5 for white. Go was the ﬁrst tremendously successful application of MCTS to games [7–9,18]. All the best current Go programs use MCTS. Knightthrough: The rules are similar to Breakthrough except that the pawns are replaced by knights that can only go forward. Misere Knightthrough: The rules are the same as for Knightthrough except that the ﬁrst player to reach the opposite row has lost. Nogo: The rules are the same as Go except that it is forbidden to capture and to commit suicide. The ﬁrst player that cannot move has lost.
Our feeling is that Havannah programs cannot be expected to play at an elite level until they learn to play a more natural, human-like game. Towards this end, we have retooled Havbot to use EPT. Evidence is still inconclusive, and more details will be provided below, but we feel that its current style of play is more natural and has the potential to improve to noticeably higher levels of play. It currently beats the mini-max version of Havbot about 60 % of the time. Breakbot, like Havbot, was written initially using MCTS but we fully expected to transition to EPT.
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