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 …

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

Potential heuristics for state-space search are defined as weighted sums over simple state
features. Atomic features consider the value of a single state variable in a factored state …

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 …

We investigate the use of relaxed decision diagrams (DDs) for computing admissible
heuristics for the cost-optimal delete-free planning (DFP) problem. Our main contributions …

We introduce transition-counting constraints as a principled tool to formalize constraints that
must hold in every solution of a transition system. We then show how to obtain transition …

In classical planning, the goal is to derive a course of actions that allows an intelligent agent
to move from any situation it finds itself in to one that satisfies its goals. Classical planning is …

Recent successes of neural networks in solving combinatorial problems and games like Go,
Poker and others inspire further attempts to use deep learning approaches in discrete …

Cost partitioning admissibly combines the information from multiple heuristics for optimal
state-space search. One of the strongest cost partitioning algorithms is saturated cost …

We explore the use of multivalued decision diagrams (MDDs) to represent a relaxation of the
state-transition graph for classical planning problems. The relaxation exploits the exact state …