Nonmonotonic Reasoning and Computational Knowledge Representation

IIS-0097278 Miroslaw Truszczynski、Raphael A.Finkel和Victor Marek肯塔基州大学146,167-12美元非单调推理和计算知识表示这是连续三年的奖项的第一年资助。PI将研究和实现基于答案集编程(ASP)范式的计算知识表示系统，并使用他最近发现的非单调逻辑，以证明该方法的实用性和有效性。逻辑最常用于知识表示，如下所示。为了解决一个问题，我们用一阶逻辑(或其片段)语言将其约束和相关的背景知识表示为理论。我们将目标(问题的陈述)表述为逻辑公式。然后，我们使用证明技术来确定这个公式是否源自理论。公式的证明、变量替换或两者兼而有之决定了解决方案。PI将采取不同的方法，研究和开发基于非单调逻辑而不是一阶逻辑的计算知识表示工具。此外，他背离了逻辑编程中占主导地位的单一意图模型方法。在ASP范式下，非单调形式主义的理论被视为集合族的规范--其预期模型的集合。每个模型都被视为不同单一解决方案的代表。PI将研究基于非单调逻辑的ASP形式化的句法和语义问题，研究使用这些形式化进行快速计算的方法，开发实际实现，并展示答案集编程引擎的有效性及其在知识表示中的适用性。如果成功，这项工作将把答案集编程确立为声明性编程的一种可行方法，这反过来将为人工智能研究人员和从业者提供新一代知识表示的计算工具。

IIS-0097278Miroslaw Truszczynski, Raphael A. Finkel and Victor MarekUniversity of Kentucky$146,167 - 12 mosNonmonotonic Reasoning and Computational Knowledge RepresentationThis is the first year funding of a three year continuing award. The PI will study and implement computational knowledge-representation systems based on the paradigm of answer-set programming (ASP) with nonmonotonic logic that he recently identified, in order to demonstrate the practicality and effectiveness of the approach. Logic is most commonly used in knowledge representation as follows. To solve a problem we represent its constraints and the relevant background knowledge as a theory in the language of first-order logic (or its fragment). We formulate the goal (the statement of the problem) as a formula of the logic. We then use proof techniques to decide whether this formula follows from the theory. A proof of the formula, variable substitutions or both determine a solution. Taking a different approach, the PI will study and develop computational knowledge representation tools based on nonmonotonic logics rather than on the first-order logic. In addition, he departs from the single-intended model approach dominant in logic programming. Under the ASP paradigm, a theory in a nonmonotonic formalism is regarded as a specification of a family of sets - a collection of its intended models. Each model is viewed as a representation of a different single solution. The PI will investigate syntactic and semantic issues of ASP formalisms based on nonmonotonic logics, study methods for fast computing with these formalisms, develop practical implementations, and demonstrate effectiveness of answer-set programming engines and their applicability in knowledge representation. If successful, the work will establish answer-set programming as a viable approach to declarative programming, which in turn will provide AI researchers and practitioners with a new generation of computational tools for knowledge representation.