Addendum to: Summary Information for Reasoning About Hierarchical Plans

TL;DR

This paper introduces new methods for deriving precondition and effect summaries from hierarchical plans, enabling more practical and effective planning with abstract and primitive actions.

Contribution

It formally defines preconditions and effects for hierarchical plans and provides algorithms for automatic derivation, enhancing hierarchical planning techniques.

Findings

Algorithms successfully derive precondition and effect summaries.

Methods improve the integration of hierarchical plans with classical planners.

Analysis shows the algorithms' properties and effectiveness.

Abstract

Hierarchically structured agent plans are important for efficient planning and acting, and they also serve (among other things) to produce "richer" classical plans, composed not just of a sequence of primitive actions, but also "abstract" ones representing the supplied hierarchies. A crucial step for this and other approaches is deriving precondition and effect "summaries" from a given plan hierarchy. This paper provides mechanisms to do this for more pragmatic and conventional hierarchies than in the past. To this end, we formally define the notion of a precondition and an effect for a hierarchical plan; we present data structures and algorithms for automatically deriving this information; and we analyse the properties of the presented algorithms. We conclude the paper by detailing how our algorithms may be used together with a classical planner in order to obtain abstract plans.