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15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'03)
Search Control Techniques for Planning
Sacramento, California, USA
November 03-November 05
ISBN: 0-7695-2038-3
Minh Tang, University of Wisconsin at Milwaukee
Amol Dattatraya Mali, University of Wisconsin at Milwaukee
Signi.cant advances have been made in heuristic search for classical planning in the last six years. Most of these planners use A* style search. We report on two sound and complete domain-independent classical planners AWA* (Adjusted Weighted A*) and MAWA* (Modified AWA*) in this paper. AWA* is the .rst planner to use node-dependent weighting in A*. MAWA* uses a two-phase heuristic evaluation. MAWA* applies node-dependent weighting to a subset of the nodes in the fringe, after the two-phase evaluation. We report on an empirical comparison of AWA*, MAWA* with classical planners AltAlt, FF and STAN 4. Both AWA* and MAWA* outperform AltAlt and STAN 4. Both AWA* and MAWA* solve many problems that FF does not. The ideas in AWA* and MAWA* are general enough to be applicable in solving other planning problems like temporal planning and planning with resources and numerical variables.
Citation:
Minh Tang, Amol Dattatraya Mali, "Search Control Techniques for Planning," ictai, pp.168, 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'03), 2003
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