In hierarchical planning, landmarks are tasks that occur on any search path leading from the initial plan to a solution. In this work, we present novel domain-independent planning strategies based on such hierarchical landmarks. Our empirical evaluation on four benchmark domains shows that these landmark-aware strategies outperform established search strategies in many cases.

Human users who execute an automatically generated plan want to understand the rationale behind it. Knowledge-rich plans are particularly suitable for this purpose, because they provide the means to give reason for causal, temporal, and hierarchical relationships between actions. Based on this information, focused arguments can be generated that constitute explanations on an appropriate level of abstraction. In this paper, we present a formal approach to plan explanation. Information about plans is represented as first-order logic formulae and explanations are constructed as proofs in the resulting axiomatic system. With that, plan explanations are provably correct w.r.t. the planning system that produced the plan. A prototype plan explanation system implements our approach and first experiments give evidence that finding plan explanations is feasible in real-time.