We propose a new graph-based spatial temporal logic for knowledge representation and automated reasoning in this paper. The proposed logic achieves a balance between expressiveness and tractability in applications such as cognitive robots. The satisfiability of the proposed logic is decidable. We apply a Hilbert style axiomatization for the proposed graph-based spatial temporal logic, in which Modus ponens and IRR are the inference rules. We show that the corresponding deduction system is sound and complete and can be implemented through SAT.

中文翻译：

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用于认知机器人知识表示和自动推理的基于图的时空逻辑

我们在本文中提出了一种新的基于图的时空逻辑，用于知识表示和自动推理。所提出的逻辑在认知机器人等应用中实现了表现力和易处理性之间的平衡。所提出的逻辑的可满足性是可判定的。我们对所提出的基于图的时空逻辑应用希尔伯特式公理化，其中 Modus ponens 和 IRR 是推理规则。我们表明相应的扣除系统是健全和完整的，可以通过 SAT 实现。