State trajectory and preference constraints are the two language features introduced in PDDL3 (Gerevini & Long 2005) for describing benchmarks of the 5th international planning competition. In this work we make existing solver technology applicable to planning with PDDL3 domains by compiling the new constructs back to PDDL2 (Fox & Long 2003). State trajectory constraints are translated into LTL formulae and further to Buechi automata, one for each constraint. These automata are compiled to grounded PDDL and the results are merged with the grounded representation of the original problem. Preference constraints are compiled away using numerical state variables. We provide encouraging experimental results in heuristic search planning.
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