On the Role of Ground Actions in Refinement Planning

Håkan L. S. Younes Reid G. Simmons

Abstract
Less than a decade ago, the focus in refinement planning was on partial order planners using lifted actions. Today, the currently most successful refinement planners are all state space planners using ground actions—i.e. actions where all parameters have been substituted by objects. In this paper, we address the role of ground actions in refinement planning, and present empirical results indicating that their role is twofold. First, planning with ground actions represents a bias towards early commitment of parameter bindings. Second, ground actions help enforce joint parameter domain constraints. By implementing these two techniques in a least commitment planner such as UCPOP, together with using an informed heuristic function to guide the search for solutions, we show that we often need to generate far fewer plans than when planning with ground action, while the number of explored plans remains about the same. In some cases a vast reduction can also be achieved in the number of explored plans.

Full paper: PDF, PS (8 pages, 18 references)
Copyright © 2002, American Association for Artificial Intelligence. All rights reserved.

Presentation: PDF (26 slides)

Citings

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