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Logic Programming for Describing and Solving Planning Problems

2000/03/08 by Maurice Bruynooghe, Bruynooghe, Maurice
Computer Science · #Artificial Intelligence (cs.AI) #D.1.6 #D.3.1 #F.4.1 #FOS: Computer and information sciences #I.2.3 #Logic in Computer Science (cs.LO) #Logic, Reasoning, and Knowledge #Logic, programming, and type systems #Multi-Agent Systems and Negotiation #cs.AI #cs.LO

paper · pdf · doi:10.48550/arxiv.cs/0003025

8 pages, no figures, Eighth International Workshop on Nonmonotonic Reasoning, special track on Representing Actions and Planning

arxiv created 2000/03/08 · openalex publication_date 2000/03/08 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

A logic programming paradigm which expresses solutions to problems as stable models has recently been promoted as a declarative approach to solving various combinatorial and search problems, including planning problems. In this paradigm, all program rules are considered as constraints and solutions are stable models of the rule set. This is a rather radical departure from the standard paradigm of logic programming. In this paper we revisit abductive logic programming and argue that it allows a programming style which is as declarative as programming based on stable models. However, within abductive logic programming, one has two kinds of rules. On the one hand predicate definitions (which may depend on the abducibles) which are nothing else than standard logic programs (with their non-monotonic semantics when containing with negation); on the other hand rules which constrain the models for the abducibles. In this sense abductive logic programming is a smooth extension of the standard paradigm of logic programming, not a radical departure.

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