Keywords: classical planning, symbolic bidirectional search, centroid states, minimum covering states
Abstract: In some scenarios, planning agents might be interested in reaching states that keep certain relationships with respect to a set of goals. Recently, two of these types of relationships were proposed: centroids, which minimize the average distance to the goals; and minimum covering states, which minimize the maximum distance to the goals. Existing approaches compute these states by searching forward either in the original or a reformulated task. In this paper, we propose several algorithms that use symbolic bidirectional search to efficiently compute centroids and minimum covering states. Experimental results in both existing and novel benchmarks show that our algorithms scale much better than previous approaches, establishing a new state of the art technique for this problem.
Category: Long
Student: No
Submission Number: 218
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