Extending Answer Set Programming

扩展答案集编程

• 批准号: RGPIN-2015-05642
• 负责人: You, JiaHuai
• 金额: $ 2.62万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=613666
• 关键词: Extending; Answer; Set; Programming

A computational problem can be solved by designing and implementing an algorithm for it, or by expressing it in an intuitive modelling language that comes with software for evaluating expressions written in the language. The latter is an example of what is called declarative problem solving. The goal of this research is to extend Answer Set Programming (ASP for short), which has emerged as a promising declarative paradigm for solving computational problems, by addressing two important problems: (a) on integrating open-world with closed-world reasoning, and (b) on using ASP as a uniform language for modeling and reasoning with domain as well as defeasible ontological knowledge. The main idea of ASP is that a given problem is stated in terms of constraints, which are expressed in a rule-based language under the stable model (also called answer set) semantics. Intuitively, an answer set corresponds to a solution to the problem being solved. When an answer set is computed, the user can extract from it the corresponding solution. The formulation of ASP has been crystallized from years of research in knowledge representation, logic programming, and constraint satisfaction. The goal is to provide a declarative language for modelling domain knowledge and computational tools for processing programs written in such a language. With highly competitive ASP solvers already built, several applications have been developed, for example, in molecular biology, decision support systems, planning and scheduling, solving puzzles and games, and more recently, in reasoning with the Web where ontological knowledge plays a critical role. In this research, we propose to study two directions of extending ASP, each with distinguished features and merits. One is on a tight integration of ASP with decidable fragments of class logic, where we will address the problem of combining open and closed world reasoning. These kind of reasoning tasks often arise in the context of reasoning with complex heterogeneous systems. One advantage of this approach is that it allows the adoption of efficient inference engines, e.g., those developed for reasoning with ontology. The other direction concerns ASP with existential rules for representing and reasoning with domain and defeasible ontological knowledge in a uniform language. This will result in a seamless integration of different kinds of reasoning and establish foundations for building the next generation ASP solvers. It is well anticipated that many further applications would require processing domain knowledge in conjunction with ontological knowledge, such as planning and scheduling, clinical trial and complex management systems, and reasoning with the Web. The success of this research will provide needed insights, and computational mechanisms, for advancing the ASP adoption in solving the next wave of new applications.

计算问题可以通过设计和实现算法来解决，或者用直观的建模语言来表达它，该语言附带用于评估用该语言编写的表达式的软件。后者是所谓的声明式问题解决的一个例子。这项研究的目标是通过解决两个重要问题来扩展答案集编程（简称 ASP），它已成为解决计算问题的一种有前途的声明性范式：（a）将开放世界与封闭世界推理相结合，以及（b）使用 ASP 作为统一语言来建模和推理领域以及可废止的本体论知识。 ASP的主要思想是用约束来描述给定的问题，这些约束在稳定模型（也称为答案集）语义下用基于规则的语言表达。直观上，答案集对应于正在解决的问题的解决方案。当计算出答案集时，用户可以从中提取相应的解决方案。 ASP 的制定是多年在知识表示、逻辑编程和约束满足方面的研究的结晶。目标是提供一种用于建模领域知识的声明性语言和用于处理用这种语言编写的程序的计算工具。随着高度竞争的 ASP 求解器的建立，一些应用程序已经开发出来，例如，在分子生物学、决策支持系统、规划和调度、解决谜题和游戏，以及最近在本体知识发挥关键作用的网络推理中。 在本研究中，我们建议研究扩展ASP的两个方向，每个方向都有独特的特点和优点。一是 ASP 与类逻辑的可判定片段的紧密集成，我们将解决开放世界推理与封闭世界推理相结合的问题。此类推理任务通常出现在复杂异构系统的推理背景中。这种方法的一个优点是它允许采用高效的推理引擎，例如为本体推理而开发的引擎。另一个方向涉及 ASP，它具有用统一语言表示和推理领域的存在规则和可废止的本体论知识。这将导致不同类型推理的无缝集成，并为构建下一代 ASP 求解器奠定基础。 预计许多进一步的应用将需要结合本体知识来处理领域知识，例如规划和调度、临床试验和复杂的管理系统以及网络推理。这项研究的成功将为推动 ASP 的采用以解决下一波新应用程序提供所需的见解和计算机制。