论文标题

具有不完整知识和感知信息的时间计划

Temporal Planning with Incomplete Knowledge and Perceptual Information

论文作者

Carreno, Yaniel, Petillot, Yvan, Petrick, Ronald P. A.

论文摘要

在现实世界应用中,推理不完整的知识,传感,时间概念和数字约束的能力至关重要。虽然几个AI计划者能够处理其中一些要求,但它们主要限于具有特定类型的约束的问题。本文提出了一种新的计划方法,该方法将临时计划构建结合在时间计划框架中,提供考虑数字约束和不完整知识的解决方案。我们建议对计划域定义语言(PDDL)进行较小的扩展,以建模(i)不完整,(ii)通过未知命题进行操作的知识传感动作,以及(iii)非确定性感应效应的可能结果。我们还引入了一组新的计划域来评估我们的求解器,该求解器在各种问题上表现出良好的性能。

In real-world applications, the ability to reason about incomplete knowledge, sensing, temporal notions, and numeric constraints is vital. While several AI planners are capable of dealing with some of these requirements, they are mostly limited to problems with specific types of constraints. This paper presents a new planning approach that combines contingent plan construction within a temporal planning framework, offering solutions that consider numeric constraints and incomplete knowledge. We propose a small extension to the Planning Domain Definition Language (PDDL) to model (i) incomplete, (ii) knowledge sensing actions that operate over unknown propositions, and (iii) possible outcomes from non-deterministic sensing effects. We also introduce a new set of planning domains to evaluate our solver, which has shown good performance on a variety of problems.

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