Planning with Reduced Operator Sets
2000 (English)In: Proceedings of the 5th International Conference on Artificial Intelligence Planning and Scheduling (AIPS) / [ed] Steve Chien, Subbarao Kambhampati, Craig A. Knoblock, AAAI Press, 2000, 150-158Conference paper (Refereed)
Classical propositional STRIPS planning is nothing but the search for a path in the state transition graph induced by the operators in the planning problem. What makes the problem hard is the size and the sometimes adverse structure of this graph. We conjecture that the search for a plan would be more efficient if there were only a small number of paths from the initial state to the goal state. To verify this conjecture, we define the notion of reduced operator sets and describe ways of finding such reduced sets. We demonstrate that some state-of-the-art planners run faster using reduced operator sets.
National CategoryComputer Science
IdentifiersURN: urn:nbn:se:liu:diva-59901ISBN: 978-1-57735-111-5OAI: oai:DiVA.org:liu-59901DiVA: diva2:354004
5th International Conference on Artificial Intelligence Planning and Scheduling (AIPS), Breckenridge, Colorado, USA, 14-17 April 2000