• DocumentCode
    2357836
  • Title

    Search control techniques for planning

  • Author

    Tang, Minh ; Mali, Amol Dattatraya

  • Author_Institution
    Electr. Eng. & Comput. Sci., Univ. of Wisconsin, Milwaukee, WI, USA
  • fYear
    2003
  • fDate
    3-5 Nov. 2003
  • Firstpage
    168
  • Lastpage
    175
  • Abstract
    Significant 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 first 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.
  • Keywords
    heuristic programming; planning (artificial intelligence); search problems; temporal reasoning; MAWA*; adjusted weighted A*; classical planning heuristic searching; domain-independent classical planner; domain-independent classical planners; heuristic evaluation; heuristic search; modified AWA*; node-dependent weighting; numerical variables; planning problem; search control; temporal planning; Artificial intelligence; Computer science; Costs; Optimal control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2003. Proceedings. 15th IEEE International Conference on
  • ISSN
    1082-3409
  • Print_ISBN
    0-7695-2038-3
  • Type

    conf

  • DOI
    10.1109/TAI.2003.1250186
  • Filename
    1250186