PLANNING PLANNING PLANNING WITH FORWARD SEARCH Planning with Resources and Concurrency A Forward Chaining Approach

Recently tremendous advances have been made in the performance of AI planning systems. However increased performance is only one of the prerequi-sites for bringing planning into the realm of real ap-plications; advances in the scope of problems that can be represented and solved must also be made. In this paper we address two important represen-tational features, concurrently executable actions with varying durations, and metric quantities like resources, both essential for modeling real appli-cations. We show how the forward chaining ap-proach to planning can be extended to allow it to solve planning problems with these two features. Forward chaining using heuristics or domain spe-cific information to guide search has shown itself to be a very promising approach to planning, and it is sensible to try to build on this success. In our experiments we utilize the TLPLAN approach to planning, in which declaratively represented con-trol knowledge is used to guide search. We show that this extra knowledge can be intuitive and easy to obtain, and that with it impressive planning per-formance can be achieved.