Classical Planning with Avoid ConditionsDownload PDF

May 18, 2021 (edited Jul 18, 2021)HSDIP 2021Readers: Everyone
  • Keywords: classical planning, heuristic search, state constraints
  • TL;DR: We explore different methods to effectively deal with avoid conditions, constraints on states that may not be part of a solution, in classical planning as heuristic search.
  • Abstract: It is often natural in planning to specify conditions that should be avoided, characterizing dangerous or highly undesirable behavior. PDDL3 supports this with temporal-logic state constraints. Here we focus on the simpler case where the constraint is a non-temporal formula $phi$ -- the avoid condition -- that must be false throughout the plan. We design techniques tackling such avoid conditions effectively. We show how to learn from search experience which states necessarily lead into $phi$, and we show how to tailor abstractions to recognize that avoiding $phi$ will not be possible starting from a given state. We run a large-scale experiment, comparing our techniques against compilation methods and against simple state pruning using $phi$. The results show that our techniques are often superior.
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