Proof-Carrying Plans: a Resource Logic for AI Planning

Alasdair Hill, Ekaterina Komendantskaya, Ronald P. A. Petrick
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引用次数: 2

Abstract

Planning languages have been used successfully in AI for several decades. Recent trends in AI verification and Explainable AI have raised the question of whether AI planning techniques can be verified. In this paper, we present a novel resource logic, the Proof Carrying Plans (PCP) logic that can be used to verify plans produced by AI planners. The PCP logic takes inspiration from existing resource logics (such as Linear logic and Separation logic) as well as Hoare logic when it comes to modelling states and resource-aware plan execution. It also capitalises on the Curry-Howard approach to logics, in its treatment of plans as functions and plan pre- and post-conditions as types. This paper presents two main results. From the theoretical perspective, we show that the PCP logic is sound relative to the standard possible world semantics used in AI planning. From the practical perspective, we present a complete Agda formalisation of the PCP logic and of its soundness proof. Moreover, we showcase the Curry-Howard, or functional, value of this implementation by supplementing it with the library that parses AI plans into Agda’s proofs automatically. We provide evaluation of this library and the resulting Agda functions. Keywords: AI planning, Verification, Resource Logics, Theorem Proving, Dependent Types.
论证计划:AI规划的资源逻辑
几十年来,规划语言已经成功地应用于人工智能领域。人工智能验证和可解释人工智能的最新趋势提出了人工智能规划技术是否可以验证的问题。在本文中,我们提出了一种新的资源逻辑,即可用于验证人工智能规划者生成的计划的携带证明计划(PCP)逻辑。当涉及到对状态建模和资源感知计划执行时,PCP逻辑从现有的资源逻辑(如线性逻辑和分离逻辑)以及Hoare逻辑中获得灵感。它还利用了Curry-Howard的逻辑方法,将计划视为函数,将计划前置条件和后置条件视为类型。本文给出了两个主要结果。从理论的角度来看,我们表明PCP逻辑相对于人工智能规划中使用的标准可能世界语义是合理的。从实践的角度出发,我们给出了PCP逻辑的完整的议程形式化及其可靠性证明。此外,我们通过将AI计划自动解析为Agda证明的库来补充它,从而展示了该实现的Curry-Howard或功能价值。我们提供了该库的评估和生成的Agda函数。关键词:人工智能规划,验证,资源逻辑,定理证明,依赖类型
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