Incremental Search for Counterexample-Guided Cartesian Abstraction Refinement
DOI:
https://doi.org/10.1609/icaps.v30i1.6667Abstract
Counterexample-guided Cartesian abstraction refinement has been shown to yield informative heuristics for optimal classical planning. The algorithm iteratively finds an abstract solution and uses it to decide how to refine the abstraction. Since the abstraction grows in each step, finding solutions is the main bottleneck of the refinement loop. We cast the refinements as an incremental search problem and show that this drastically reduces the time for computing abstractions.
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Published
2020-06-01
How to Cite
Seipp, J., von Allmen, S., & Helmert, M. (2020). Incremental Search for Counterexample-Guided Cartesian Abstraction Refinement. Proceedings of the International Conference on Automated Planning and Scheduling, 30(1), 244-248. https://doi.org/10.1609/icaps.v30i1.6667