English

Addendum to: Summary Information for Reasoning About Hierarchical Plans

Artificial Intelligence 2017-08-11 v1

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.

Cite

@article{arxiv.1708.03019,
  title  = {Addendum to: Summary Information for Reasoning About Hierarchical Plans},
  author = {Lavindra de Silva and Sebastian Sardina and Lin Padgham},
  journal= {arXiv preprint arXiv:1708.03019},
  year   = {2017}
}

Comments

This paper is a more detailed version of the following publication: Lavindra de Silva, Sebastian Sardina, Lin Padgham: Summary Information for Reasoning About Hierarchical Plans. ECAI 2016: 1300-1308

R2 v1 2026-06-22T21:10:58.390Z