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Learning Interpretable Heuristics for WalkSAT
The performance of these algorithms crucially depends on heuristics for setting noise parameters and scoring variables.
Extracting Lifted Mutual Exclusion Invariants from Temporal Planning Domains
We show that, in turn, this reduction in the number of variables reflects positively on the performance of a number of temporal planners that use a variable/value representation by significantly reducing their running time.
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