Fragment-Based Planning Using Column Generation
نویسندگان
چکیده
We introduce a novel algorithm for temporal planning in Golog using shared resources, and describe the Bulk Freight Rail Scheduling Problem, a motivating example of such a temporal domain. We use the framework of column generation to tackle complex resource constrained temporal planning problems that are beyond the scope of current planning technology by combining: the global view of a linear programming relaxation of the problem; the strength of search in finding action sequences; and the domain knowledge that can be encoded in a Golog program. We show that our approach significantly outperforms state-of-the-art temporal planning and constraint programming approaches in this domain, in addition to existing temporal Golog implementations. We also apply our algorithm to a temporal variant of blocksworld where our decomposition speeds proof of optimality significantly compared to other anytime algorithms. We discuss the potential of the underlying algorithm being applicable to STRIPS planning, with further work.
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تاریخ انتشار 2014