Planning as Theorem Proving with Heuristics

Mikhail Soutchanski; Ryan Young

Planning as Theorem Proving with Heuristics

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arxiv 2303.13638 v3 pith:GFRWX2LC submitted 2023-03-23 cs.AI cs.LO

Mikhail Soutchanski , Ryan Young This is my paper · ORCID

classification cs.AIcs.LO

keywords heuristicplanningprovingtheoremtplhbfwscalculuslifted

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Planning as theorem proving in situation calculus was abandoned 50 years ago as an impossible project. But we have developed a Theorem Proving Lifted Heuristic (TPLH) planner that searches for a plan in a tree of situations using the A* search algorithm. It is controlled by a delete relaxation-based domain independent heuristic. We compare TPLH with Fast Downward (FD) and Best First Width Search (BFWS) planners over several standard benchmarks. Since our implementation of the heuristic function is not optimized, TPLH is slower than FD and BFWS. But it computes shorter plans, and it explores fewer states. We discuss previous research on planning within KR\&R and identify related directions. Thus, we show that deductive lifted heuristic planning in situation calculus is actually doable.

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