Coles, Andrew Ian

Karpas, Erez

Ruml, Wheeler

Shimony, Solomon

Shperberg, Shahaf

English

Heuristic search research often deals with finding algorithms for offline planning which aim to minimize the number of expanded nodes or planning time. In online planning, algorithms for real-time search or deadline-aware search have been considered before. However, in this paper, we are interested in the problem of situated temporal planning in which an agent's plan can depend on exogenous events in the external world, and thus it becomes important to take the passage of time into account during the planning process. Previous work on situated temporal planning has proposed simple pruning strategies, as well as complex schemes for a simplified version of the associated metareasoning problem. In this paper, we propose a simple metareasoning technique, called the crude greedy scheme, that can be applied in a situated temporal planner. Our empirical evaluation shows that the crude greedy scheme outperforms standard heuristic search based on cost-to-go estimates

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Beyond Cost-to-go Estimates in Situated Temporal Planning

https://kclpure.kcl.ac.uk/portal/files/110566422/Metareasoning_for_Situated_Temporal_Planning.pdf

Beyond Cost-to-go Estimates in Situated Temporal Planning

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