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Titlebook: Computers and Games; 7th International Co H. Jaap Herik,Hiroyuki Iida,Aske Plaat Conference proceedings 2011 The Editor(s) (if applicable)

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11#
發(fā)表于 2025-3-23 10:09:06 | 只看該作者
Consultation Algorithm for Computer Shogi: Move Decisions by Majority,ividual players. A method that can create multiple players from one program is presented. Applying a simple rule to select a decision on a single move, the consultation algorithm improves the performance of computer Shogi engines. It is also demonstrated that a council system consisting of three wel
12#
發(fā)表于 2025-3-23 17:50:36 | 只看該作者
Optimistic Selection Rule Better Than Majority Voting System, where each player uses a different series of pseudo-random numbers. A combination of multiple players under the majority voting system would improve the performance of a Shogi-playing computer. We present a new strategy of move selection based on the search values of a number of players. The move d
13#
發(fā)表于 2025-3-23 21:21:41 | 只看該作者
Knowledge Abstraction in Chinese Chess Endgame Databases,o the main memory of a computer during tournaments. In this paper, a novel knowledge abstraction strategy is proposed to compress endgame databases. The goal is to obtain succinct knowledge for practical endgames. A specialized goal-oriented search method is described and applied on the important en
14#
發(fā)表于 2025-3-24 01:17:44 | 只看該作者
15#
發(fā)表于 2025-3-24 06:01:25 | 只看該作者
A Markovian Process Modeling for Pickomino, has to make the best decisions first to choose the dice to keep, then to choose between continuing or stopping depending on the previous rolls and on the available resources. Markov Decision Processes (MDPs) offer the formal framework to model this game. The two main problems are first to determine
16#
發(fā)表于 2025-3-24 07:14:55 | 只看該作者
17#
發(fā)表于 2025-3-24 12:54:01 | 只看該作者
18#
發(fā)表于 2025-3-24 18:50:24 | 只看該作者
19#
發(fā)表于 2025-3-24 20:24:29 | 只看該作者
20#
發(fā)表于 2025-3-25 03:14:50 | 只看該作者
https://doi.org/10.1007/978-3-7908-1932-8the proof and disproof number of a leaf node with the help of a heuristic evaluation function. Experiments in LOA and Surakarta show that compared to PN and PN., which use mobility to initialize the proof and disproof numbers, EF-PN and EF-PN. take between 45% to 85% less time for solving positions.
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