  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.
