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Addressing NP-Complete Puzzles with Monte-Carlo Methods

机译:用Monte-Carlo方法解决NP完整的谜题

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摘要

NP-complete problems are a challenging task for researchers, who investigate tractable versions and attempt to generalise the methods used for solving them. Over the years a large set of successful standard methods have been developed. We mention A and IDA which have proven to be reasonably successful in solving a set of NP-complete problems, particularly single-agent games (puzzles). However, sometimes these methods do not work well. The intriguing question then is whether there are new methods that will help us out. In this paper we investigate whether Monte-Carlo Tree-Search (MCTS) is an interesting alternative. We propose a new MCTS variant, called Single-Player Monte-Carlo Tree-Search (SP-MCTS). Our domain of research is the puzzle SameGame. It turned out that our SP-MCTS program gained the highest scores so far on the standardised test set. So, SP-MCTS can be considered as a new method for addressing NP-complete puzzles successfully.
机译:NP-Complete问题对于研究人员来说是一个具有挑战性的任务,他调查了易旧的版本并试图概括用于解决它们的方法。多年来,已经开发了大量成功的标准方法。我们提到A和IDA,在解决一系列NP完整问题,特别是单颗粒式游戏(难题)方面被证明是合理成功的。但是,有时这些方法不起作用。那么有趣的问题是是否有新方法可以帮助我们出去。在本文中,我们调查Monte-Carlo树搜索(MCT)是一个有趣的替代方案。我们提出了一个新的MCT变体,称为单人蒙特卡罗树搜索(SP-MCTS)。我们的研究领域是拼图别人。事实证明,我们的SP-MCTS计划迄今为止标准化测试集获得了最高分数。因此,SP-MCT可以被视为成功寻址NP完整难题的新方法。

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