plasp 3: Towards Effective ASP Planning

Abstract

We describe the new version of the Planning Domain Definition Language (PDDL)-to-Answer Set Programming (ASP) translator plasp. First, it widens the range of accepted PDDL features. Second, it contains novel planning encodings, some inspired by Satisfiability Testing (SAT) planning and others exploiting ASP features such as well-foundedness. All of them are designed for handling multivalued fluents in order to capture both PDDL as well as SAS planning formats. Third, enabled by multishot ASP solving, it offers advanced planning algorithms also borrowed from SAT planning. As a result, plasp provides us with an ASP-based framework for studying a variety of planning techniques in a uniform setting. Finally, we demonstrate in an empirical analysis that these techniques have a significant impact on the performance of ASP planning.

Logic programming for deliberative robotic task planning

“…A non-monotonic logic programming language with similar syntax to Prolog is Answer Set Programming (ASP) (Calimeri et al 2020). Introduced by Marek and Truszczyński (1999), ASP was first proposed in Lifschitz (1999) to solve the planning problem for autonomous agents, as applied, e.g., by Dimopoulos et al (2019). ASP is based on the stable model semantics (Gelfond and Lifschitz 1988).…”