Specifying and Exploiting Non-Monotonic Domain-Specific Declarative Heuristics in Answer Set Programming

IF 4.5 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Artificial Intelligence Research Pub Date : 2022-09-19 DOI:10.1613/jair.1.14091
Richard Comploi-Taupe, G. Friedrich, Konstantin Schekotihin, A. Weinzierl
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引用次数: 1

Abstract

Domain-specific heuristics are an essential technique for solving combinatorial problems efficiently. Current approaches to integrate domain-specific heuristics with Answer Set Programming (ASP) are unsatisfactory when dealing with heuristics that are specified non-monotonically on the basis of partial assignments. Such heuristics frequently occur in practice, for example, when picking an item that has not yet been placed in bin packing. Therefore, we present novel syntax and semantics for declarative specifications of domain-specific heuristics in ASP. Our approach supports heuristic statements that depend on the partial assignment maintained during solving, which has not been possible before. We provide an implementation in Alpha that makes Alpha the first lazy-grounding ASP system to support declaratively specified domain-specific heuristics. Two practical example domains are used to demonstrate the benefits of our proposal. Additionally, we use our approach to implement informed search with A*, which is tackled within ASP for the first time. A* is applied to two further search problems. The experiments confirm that combining lazy-grounding ASP solving and our novel heuristics can be vital for solving industrial-size problems.
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答案集规划中非单调域特定声明启发式的指定与利用
特定领域启发式是有效求解组合问题的一种重要技术。当前将领域特定启发式与答案集规划(ASP)相结合的方法在处理基于部分分配的非单调指定启发式时是不令人满意的。这种启发式方法在实践中经常出现,例如,在挑选尚未放入垃圾箱包装的物品时。因此,我们为ASP中特定于领域的启发式的声明性规范提出了新的语法和语义。我们的方法支持启发式语句,这些启发式语句依赖于求解过程中维护的部分赋值,这在以前是不可能的。我们在Alpha中提供了一个实现,使Alpha成为第一个支持声明式指定的特定于领域的启发式的延迟基础ASP系统。使用两个实际示例域来演示我们的建议的好处。此外,我们使用我们的方法来实现带有A*的知情搜索,这是第一次在ASP中解决。A*应用于两个进一步的搜索问题。实验证实,将懒惰基础ASP求解方法与我们的新启发式方法相结合,对于解决工业规模的问题至关重要。
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来源期刊
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research 工程技术-计算机:人工智能
CiteScore
9.60
自引率
4.00%
发文量
98
审稿时长
4 months
期刊介绍: JAIR(ISSN 1076 - 9757) covers all areas of artificial intelligence (AI), publishing refereed research articles, survey articles, and technical notes. Established in 1993 as one of the first electronic scientific journals, JAIR is indexed by INSPEC, Science Citation Index, and MathSciNet. JAIR reviews papers within approximately three months of submission and publishes accepted articles on the internet immediately upon receiving the final versions. JAIR articles are published for free distribution on the internet by the AI Access Foundation, and for purchase in bound volumes by AAAI Press.
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