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

答案集编程（ASP）是声明性编程的一种最新形式，已应用于许多知识密集型任务，如产品配置、计划、诊断和信息集成。像其他计算范式一样，如SAT（可满足性检查）和CP（约束规划），ASP为形式化和解决各种问题提供了一个共同的基础，但与其他范式不同的是，它侧重于知识表示，并已被证明对快速原型设计很有用。虽然对ASP的研究产生了许多有希望的结果，但它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）合并，并探索它们之间的协同作用，来克服这些局限性。该项目旨在为ASP与其他计算范式的关系提供一种变革性的理解，以增强ASP的推理能力并拓宽其有效的领域。在知识表示方面，本研究将阐明ASP作为一种主要的知识表示形式，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。

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.