FAPE: a Constraint-based Planner for Generative and Hierarchical Temporal Planning

TL;DR

FAPE is a novel temporal planner that combines expressive timeline features with hierarchical control, using reachability analysis and causal networks to improve search efficiency and outperform less expressive planners.

Contribution

It introduces a constraint-based planning approach that integrates flexible timelines with hierarchical refinement and a new reachability analysis technique for efficient search.

Findings

FAPE is competitive with less expressive planners.

Hierarchical control knowledge improves performance.

Experimental results validate the approach on benchmark problems.

Abstract

Temporal planning offers numerous advantages when based on an expressive representation. Timelines have been known to provide the required expressiveness but at the cost of search efficiency. We propose here a temporal planner, called FAPE, which supports many of the expressive temporal features of the ANML modeling language without loosing efficiency. FAPE's representation coherently integrates flexible timelines with hierarchical refinement methods that can provide efficient control knowledge. A novel reachability analysis technique is proposed and used to develop causal networks to constrain the search space. It is employed for the design of informed heuristics, inference methods and efficient search strategies. Experimental results on common benchmarks in the field permit to assess the components and search strategies of FAPE, and to compare it to IPC planners. The results show the proposed approach to be competitive with less expressive planners and often superior when hierarchical control knowledge is provided. FAPE, a freely available system, provides other features, not covered here, such as the integration of planning with acting, and the handling of sensing actions in partially observable environments.