RI: Small: Enhancing Nonmonotonic Declarative Knowledge Representation and Reasoning by Merging Answer Set Programming with Other Computing Paradigms

RI：小：通过将答案集编程与其他计算范式合并来增强非单调声明性知识表示和推理

• 批准号: 0916116
• 负责人: Joohyung Lee
• 金额: $ 27.5万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0916116&HistoricalAwards=false
• 关键词: RI; Small; Enhancing; Nonmonotonic; Declarative

Answer Set Programming (ASP) is a recent form of declarative programming that has been applied to many knowledge-intensive tasks, such as product configuration, planning, diagnosis, and information integration. Like other computing paradigms, such as SAT (Satisfiability Checking) and CP (Constraint Programming), ASP provides a common basis for formalizing and solving various problems, but is distinct from others in that it focuses on knowledge representation and has proved to be useful for rapid prototyping. While the research on ASP has produced many promising results, it has also identified serious limitations.The project aims at overcoming the limitations by merging ASP with other computing paradigms, such as satisfiability checking, first-order logic and constraint programming, and exploring the synergy between them. This project is expected to provide a transformative understanding of ASP's relation to other computing paradigms, to enhance ASP's reasoning capability and broaden the areas in which it is effective. Within knowledge representation, the study will clarify the role of ASP as a major knowledge representation formalism with effective computation methods that combines various methods available in other computing paradigms.

答案集编程 (ASP) 是声明式编程的最新形式，已应用于许多知识密集型任务，例如产品配置、规划、诊断和信息集成。与 SAT（可满足性检查）和 CP（约束编程）等其他计算范式一样，ASP 为形式化和解决各种问题提供了共同的基础，但与其他计算范式的不同之处在于它侧重于知识表示，并已被证明对于快速原型制作。虽然 ASP 的研究取得了许多有希望的成果，但也发现了严重的局限性。该项目旨在通过将 ASP 与其他计算范式（如可满足性检查、一阶逻辑和约束规划）相结合来克服这些局限性，并探索协同作用他们之间。该项目预计将提供对 ASP 与其他计算范式的关系的变革性理解，增强 ASP 的推理能力并拓宽其有效领域。在知识表示中，该研究将阐明 ASP 作为主要知识表示形式主义的作用，其有效的计算方法结合了其他计算范式中可用的各种方法。