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首页> 外文会议>International Symposium on Intelligence Computation amp; Applications(ISICA'2007); 20070921-23; Wuhan(CN) >An Tableau Automated Theorem Proving Method Using Logical Reinforcement Learning
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An Tableau Automated Theorem Proving Method Using Logical Reinforcement Learning

机译：使用逻辑强化学习的Tableau自动定理证明方法

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摘要

Logical reinforcement learning (LORRL) is presented with the combination of reinforcement learning and logic programming. Tableau method based on logic reinforcement learning is provided according to the real problem of tableau automated theorem proving method that need to extend for different logic formulae and it will influence the automated theorem proving efficiency. This method takes the combination of logic formulae and expansion result as abstract state, expansion rules as actions, node closes as the aim and receives a reward. On the one hand the method is suitable for a lot of types of tableau automated theorem proving and the blindness of reasoning is reduced. On the other hand simple automated theorem proving result can be used in complicated automated theorem proving and efficiency is raised.
机译：逻辑强化学习（LORRL）与强化学习和逻辑编程相结合。针对Tableau自动定理证明方法的实际问题，需要针对不同的逻辑公式进行扩展，提出了一种基于逻辑强化学习的Tableau方法，它将影响自动定理证明的效率。该方法将逻辑公式和扩展结果的组合作为抽象状态，将扩展规则作为操作，将结点作为目标并获得奖励。一方面，该方法适用于许多类型的场景自动定理证明，并且减少了推理的盲目性。另一方面，简单的自动定理证明结果可以用于复杂的自动定理证明，并提高了效率。

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