AbstractAbstractions and landmarks are two of the key mechanisms for devising admissible heuristics for domain-independent planning. Here we aim at combining them by integrating landmark information into abstractions. We propose a concrete scheme for compiling landmarks into the problem specification. This scheme, which preserves all reachable properties of the original problem, is especially suited to implicit abstraction heuristics. Our formal and empirical analysis shows that landmark information can substantially improve the quality of heuristic estimates
Planning problems are usually modeled using lifted representations, they specify predicates and acti...
The paper generalises the notion of landmarks for reasoning about planning problems involving propos...
Many known planning tasks have inherent constraints concerning the best order in which to achieve th...
Abstractions and landmarks are two powerful mechanisms for devising admissible heuristics for classi...
Current heuristic estimators for classical domain-independent planning are usually based on one of f...
Landmarks for propositional planning tasks are variable as-signments that must occur at some point i...
Current heuristic estimators for classical domain-independent planning are usually based on one of f...
Landmark heuristics are perhaps the most accurate current known admissible heuristics for optimal pl...
The identification of important planning subgoals, referred to as landmarks, has been shown to be us...
We have recently shown how counterexample-guided abstraction refinement can be used to derive inform...
Abstraction heuristics are the state of the art in optimal classical planning as heuristic search. A...
Landmarks of a planning task denote properties that must be satisfied by all plans. Existing landmar...
The planner GRAPHPLAN is based on an efficient propagation of reachability information which then ef...
In this paper, we revisit the idea of splitting a planning problem into subproblems hopefully eas-ie...
Several approaches exist to solve Artificial Intelligence planning problems, but little attention ha...
Planning problems are usually modeled using lifted representations, they specify predicates and acti...
The paper generalises the notion of landmarks for reasoning about planning problems involving propos...
Many known planning tasks have inherent constraints concerning the best order in which to achieve th...
Abstractions and landmarks are two powerful mechanisms for devising admissible heuristics for classi...
Current heuristic estimators for classical domain-independent planning are usually based on one of f...
Landmarks for propositional planning tasks are variable as-signments that must occur at some point i...
Current heuristic estimators for classical domain-independent planning are usually based on one of f...
Landmark heuristics are perhaps the most accurate current known admissible heuristics for optimal pl...
The identification of important planning subgoals, referred to as landmarks, has been shown to be us...
We have recently shown how counterexample-guided abstraction refinement can be used to derive inform...
Abstraction heuristics are the state of the art in optimal classical planning as heuristic search. A...
Landmarks of a planning task denote properties that must be satisfied by all plans. Existing landmar...
The planner GRAPHPLAN is based on an efficient propagation of reachability information which then ef...
In this paper, we revisit the idea of splitting a planning problem into subproblems hopefully eas-ie...
Several approaches exist to solve Artificial Intelligence planning problems, but little attention ha...
Planning problems are usually modeled using lifted representations, they specify predicates and acti...
The paper generalises the notion of landmarks for reasoning about planning problems involving propos...
Many known planning tasks have inherent constraints concerning the best order in which to achieve th...