Modular and taxonomic representations for tractable reasoning about actions

人工智能研究的一个长期存在的基本问题是：发展一种全面和通用的理论，用于表示和有效推理在不确定和不完全已知的大规模领域中操作的代理的行为。拟议的研究将有助于实现这一长期目标，方法是诱导结构化逻辑表示，并随后对它们进行阐述，以确保在结构化领域中进行有效的推理。所提出的研究侧重于用顺序排序的一阶逻辑和基于描述逻辑的语言来表示动作。提出的研究计划的主要目标是发展那些可以被描述为模块化、分类学或结构性的动作表征及其效果的理论发展，以及对这些表征在解决常见推理任务方面的实验评估。这项研究具有原创性和创新性，原因有几个。首先，它强调开发利用应用程序域的声明性结构的操作的逻辑理论：操作和对象的分类。其次，提出将关于动作和关于对象的分类推理与有序逻辑和模块化描述逻辑本体相结合。最后，它建议使用这些表征杠杆来解决人工智能中具有挑战性和重要的问题，包括决策理论规划和学习。虽然拟议的研究计划将有助于推进我们的知识，但它也具有开发新的逻辑框架、信息技术(以及随后的软件产品)的重大前景，这些技术将与包括医疗保健、语义网服务和工业在内的广泛应用程序相关。

A long standing and fundamental problem of AI research is this: the development of a comprehensive and general theory for representation and efficient reasoning about actions of agents operating in uncertain and incompletely known large-scale domains. The proposed research will contribute towards this long-term goal by eliciting structured logical representations and subsequently elaborating them to guarantee efficient reasoning in structured domains. The proposed research focuses on representations of actions formulated in order-sorted first order logic and in description logic-based languages. The primary objective of the proposed research program is the theoretical development of those representations of actions and their effects that can be characterized as modular, taxonomic or structural and the experimental assessment of these representations on solving the common reasoning tasks. This research is original and innovative for several reasons. First, it emphasizes the development of logical theories of actions that exploit the declarative structure of application domains: taxonomies of actions and objects. Second, it proposes to integrate taxonomic reasoning about actions and about objects with order-sorted logics and modular description logic ontologies. Finally, it proposes to use these representational leverages to solving challenging and important problems in AI, including decision-theoretic planning and learning. While the proposed research program will help to advance our knowledge, it also has a significant promise of developing new logical frameworks, information technologies (and subsequently, software products) that will be relevant for a broad range of applications including health-care, Semantic Web services and industry.