Speeding up problem solving by abstraction: a graph oriented approach
Artificial Intelligence - Special volume on empirical methods
Multi-Hierarchical Representation of Large-Scale Space: Applications to Mobile Robots
Multi-Hierarchical Representation of Large-Scale Space: Applications to Mobile Robots
Partial pathfinding using map abstraction and refinement
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Graph abstraction in real-time heuristic search
Journal of Artificial Intelligence Research
Dynamic control in real-time heuristic search
Journal of Artificial Intelligence Research
Constraint optimization and abstraction for embedded intelligent systems
CPAIOR'08 Proceedings of the 5th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
New methods for proving the impossibility to solve problems through reduction of problem spaces
Annals of Mathematics and Artificial Intelligence
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A variety of techniques have been introduced over the last decade for abstracting search graphs and then using these abstractions for search. While some basic work has been done to predict the value of an abstraction mechanism, the results have not been validated in practice. In this paper we analyze a variety of old and new abstraction mechanisms in a pathfinding testbed and show that the work done in abstraction-based refinement-style search can be predicted by the diameter and size of abstract nodes.