5 accepted papers
In cost-optimal planning, dominance pruning methods discard states during the search that are dominated by others. However, the binary nature of pruning fails to exploit information when we cannot prove that a state is fully dominated. To this end, we introduce qualified dominance, an automatic meth
Counterexample-Guided Abstraction Refinement (CEGAR) is a prominent technique to generate Cartesian abstractions for guiding search in cost- optimal planning. The core idea is to iteratively refine the abstraction, finding a flaw of the current optimal abstract plan. All existing approaches find the…
Macro-operators are a common reformulation method in planning that adds high-level operators corresponding to a fixed sequence of primitive operators. We introduce meta-operators, which allow using different sequences of actions in each state. We show how to automatically verify whether a meta-opera…
State-space search is paramount for intelligent decision making when long-term thinking is needed. We introduce dominance and contrastive analysis methods, which enable reasoning about the relative advantages among different courses of action. This re-shapes how agents reason and leads to new famili…
Polynomial-time heuristic functions for planning are commonplace since 20 years. But polynomial-time in which input? Almost all existing approaches are based on a grounded task representation, not on the actual PDDL input which is exponentially smaller. This limits practical applicability to cases w…