Many planning domains have to deal with temporal features that can be expressed using durations that are associated to actions. Unfortunately, the conservative model of actions used in many existing temporal planners is not adequate for domains which require more expressive models. This paper presents a temporal planning approach that combines the principles of Graphplan and TGP and uses the information calculated in the planning graph to deal with a non-conservative model of actions that include local conditions and effects. In this approach, we propose two strategies for search. The first one is based on the Graphplan backward search. The second one is based on a least-commitment and heuristic search, and it attempts to overcome the main limitations of a chronological backtracking search when dealing with large temporal problems. This search has proved to be beneficial in the scalability of the planner and the experiments show that a planner using this new search is competitive with other state-of-the-art planners w.r.t. the plan quality 1 .
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