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Getting the Most Out of Pattern Databases for Classical Planning

2019-11-11 | |  60 |   32 |   0

Abstract The iPDB procedure by Haslum et al. is the stateof-the-art method for computing additive abstraction heuristics for domain-independent planning. It performs a hill-climbing search in the space of pattern collections, combining information from multiple patterns in the so-called canonical heuristic. We show how stronger heuristic estimates can be obtained through linear programming. An experimental evaluation demonstrates the strength of the new technique on the IPC benchmark suite.

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