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Titlebook: Computer Games; Third Workshop on Co Tristan Cazenave,Mark H. M. Winands,Yngvi Bj?rnsso Conference proceedings 2014 Springer International

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樓主: enamel
31#
發(fā)表于 2025-3-26 22:16:06 | 只看該作者
Coordinating Dialogue Systems and Stories through Behavior Composition, of transition systems, on which behavior composition is based, in video game development, and (.) the fact that behavior composition extends the spectrum of approaches for non-linear storylines by introducing a new paradigm based on planning for a target desired process instead of a goal state. Mor
32#
發(fā)表于 2025-3-27 02:13:52 | 只看該作者
Job-Level Algorithms for Connect6 Opening Position Analysis,nalyze the suitability of these metrics when choosing best moves for a set of benchmark positions. The results show that for both metrics this node count heuristic metric for JL-UCT outperforms all the others, including the four for JL-PNS.
33#
發(fā)表于 2025-3-27 09:16:09 | 只看該作者
Monte-Carlo Tree Search and Minimax Hybrids with Heuristic Evaluation Functions,in the domains of Othello, Breakthrough, and Catch the Lion. Results showed that introducing minimax search is effective for heuristic node priors in Othello and Catch the Lion. The MCTS-minimax hybrids are also found to work well in combination with each other. For their basic implementation in thi
34#
發(fā)表于 2025-3-27 10:09:45 | 只看該作者
35#
發(fā)表于 2025-3-27 14:44:54 | 只看該作者
https://doi.org/10.1057/9781137494085in the domains of Othello, Breakthrough, and Catch the Lion. Results showed that introducing minimax search is effective for heuristic node priors in Othello and Catch the Lion. The MCTS-minimax hybrids are also found to work well in combination with each other. For their basic implementation in thi
36#
發(fā)表于 2025-3-27 18:16:34 | 只看該作者
37#
發(fā)表于 2025-3-27 22:28:34 | 只看該作者
38#
發(fā)表于 2025-3-28 03:45:48 | 只看該作者
39#
發(fā)表于 2025-3-28 07:04:26 | 只看該作者
40#
發(fā)表于 2025-3-28 13:25:47 | 只看該作者
,Minimizing?Simple?and?Cumulative?Regret in?Monte-Carlo?Tree?Search,her down the tree. We discuss the motivation for this new search technique, and show the performance of H-MCTS in six distinct two-player games: Amazons, AtariGo, Ataxx, Breakthrough, NoGo, and Pentalath.
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