Combining Domain-Independent Planning and HTN Planning: The Duet Planner

  • Authors:

  • Alfonso Gerevini;Ugur Kuter;Dana Nau;Alessandro Saetti;Nathaniel Waisbrot

  • Affiliations:

  • Dipartimento di Elettronica per l'Automazione, Universitá degli Studi di Brescia, Via Branze 38, I-25123 Brescia, Italy;Department of Computer Science and Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland 20742, USA;Department of Computer Science and Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland 20742, USA;Dipartimento di Elettronica per l'Automazione, Universitá degli Studi di Brescia, Via Branze 38, I-25123 Brescia, Italy;Department of Computer Science and Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland 20742, USA

  • Venue:
  • Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
  • Year:
  • 2008

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Abstract

Despite the recent advances in planning for classical domains, the question of how to use domain knowledge in planning is yet to be completely and clearly answered. Some of the existing planners use domain-independent search heuristics, and some others depend on intensively-engineered domain-specific knowledge to guide the planning process. In this paper, we describe an approach to combine ideas from both of the above schools of thought. We present Duet, our planning system that incorporates the ability of using hierarchical domain knowledge in the form of Hierarchical Task Networks (HTNs) as in SHOP2 [14] and using domain-independent local search techniques as in LPG [8]. In our experiments, Duet was able to solve much larger problems than LPG could solve, with only minimal domain knowledge encoded in HTNs (much less domain knowledge than SHOP2 needed to solve those problems by itself).