Laura Sebastia, Eva Onaindia, Eliseo Marzal
In this paper we show that despite the great success of some planning approaches, partial-order planning is still an efficient and valid approach for tackling planning problems. The goal of this paper is to show that the effort needed by a partial-order planner (POP) to solve a problem can be dramatically reduced. By properly exploiting the problem knowledge it is possible to obtain an approximate plan which is afterwards used as initial plan input to a POP. This plan will always contain actions which must necessarily appear in a valid solution and, therefore, the task of the POP will be simply to add the missing actions thus leading to a significant reduction in search space. In this paper, we will focus on the modifications achieved on a standard partial-order planner to adapt it to this new planning approach.
Keywords: planning, knowledge adquisition
Citation: Laura Sebastia, Eva Onaindia, Eliseo Marzal: A Graph-based Approach for POCL Planning. In W.Horn (ed.): ECAI2000, Proceedings of the 14th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2000, pp.531-535.