Counterexample-guided abstraction refinement (CEGAR) is a method for incrementally
computing abstractions of transition systems. We propose a CEGAR algorithm for computing …

A pattern database (PDB) for a planning task is a heuristic function in the form of a lookup
table that contains optimal solution costs of a simplified version of the task. In this paper we …

Counterexample-Guided Abstraction Refinement (CEGAR) is a prominent technique to
generate Cartesian abstractions for guiding search in cost-optimal planning. The core idea …

We describe a new algorithm for generating pattern collections for pattern database
heuristics in optimal classical planning. The algorithm uses the counterexample-guided …

This planner abstract describes “Scorpion 2023”, the planner configuration we submitted to
the sequential optimization track of the International Planning Competition 2023. Scorpion …

Cost partitioning is a general and principled approach for constructing additive admissible
heuristics for state-space search. Cost partitioning approaches for optimal classical planning …

Cost partitioning is the foundation of today's strongest heuristics for optimal classical
planning. However, computing a cost partitioning for each evaluated state is prohibitively …

Cost partitioning is a method for admissibly adding multiple heuristics for state-space
search. Saturated cost partitioning considers the given heuristics in sequence, assigning to …

Cost partitioning is a general method for adding multiple heuristic values admissibly. In the
setting of optimal classical planning, saturated cost partitioning has recently been shown to …

Pattern databases are the foundation of some of the strongest admissible heuristics for
optimal classical planning. Experiments showed that the most informative way of combining …