Dead-end detection is a key challenge in automated planning, and it is rapidly growing in popularity. Effective dead-end detection techniques can have a large impact on the strength of a planner, and so the effective computation of dead-ends is central to many planning approaches. One of the better understood techniques for detecting dead-ends is to focus on the delete relaxation of a planning problem, where dead-end detection is a polynomial-time operation. In this work, we provide a logical characterization for not just a single dead-end, but for every delete-relaxed dead-end in a planning problem. With a logical representation in hand, one could compile the representation into a form amenable to effective reasoning. We lay the ground-wor...
The currently dominant approach to domain-independent planning is planning as heuristic search, with...
Heuristic functions based on the delete relaxation compute upper and lower bounds on the optimal del...
Heuristic functions based on the delete relaxation compute upper and lower bounds on the optimal del...
In this work, we investigate the computation of optimal plans for delete-free tasks using relaxed de...
We establish a novel relation between delete-free planning, an important task for the AI planning co...
Planning is a central research area in artificial intelligence, and a lot of effort has gone into co...
International audienceRelaxation is ubiquitous in the practical resolution of combinatorial problems...
The currently dominant approach to domain-independent planning is planning as heuristic search, with...
The results of the latest International Probabilistic Planning Competition (IPPC-2008) indicate that...
International audienceHeuristics based on the delete relaxation are at the forefront of modern domai...
Abstract. Landmarks for a planning problem are subgoals that are necessarily made true at some point...
The automatic derivation of heuristic functions for guiding the search for plans is a fundamental te...
We consider the problem of deriving formulas that capture traps, invariants, and dead-ends in classi...
AbstractThe automatic derivation of heuristic functions for guiding the search for plans is a fundam...
In recent years, heuristic search methods for classical plan-ning have achieved remarkable results. ...
The currently dominant approach to domain-independent planning is planning as heuristic search, with...
Heuristic functions based on the delete relaxation compute upper and lower bounds on the optimal del...
Heuristic functions based on the delete relaxation compute upper and lower bounds on the optimal del...
In this work, we investigate the computation of optimal plans for delete-free tasks using relaxed de...
We establish a novel relation between delete-free planning, an important task for the AI planning co...
Planning is a central research area in artificial intelligence, and a lot of effort has gone into co...
International audienceRelaxation is ubiquitous in the practical resolution of combinatorial problems...
The currently dominant approach to domain-independent planning is planning as heuristic search, with...
The results of the latest International Probabilistic Planning Competition (IPPC-2008) indicate that...
International audienceHeuristics based on the delete relaxation are at the forefront of modern domai...
Abstract. Landmarks for a planning problem are subgoals that are necessarily made true at some point...
The automatic derivation of heuristic functions for guiding the search for plans is a fundamental te...
We consider the problem of deriving formulas that capture traps, invariants, and dead-ends in classi...
AbstractThe automatic derivation of heuristic functions for guiding the search for plans is a fundam...
In recent years, heuristic search methods for classical plan-ning have achieved remarkable results. ...
The currently dominant approach to domain-independent planning is planning as heuristic search, with...
Heuristic functions based on the delete relaxation compute upper and lower bounds on the optimal del...
Heuristic functions based on the delete relaxation compute upper and lower bounds on the optimal del...