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Fast and Informed Action Selection for Planning with Sensing

  • Alexandre Albore
  • Héctor Palacios
  • Hector Geffner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4788)

Abstract

Consider a robot whose task is to pick up some colored balls from a grid, taking the red balls to a red spot, the blue balls to a blue spot and so on, one by one, without knowing either the location or color of the balls but having a sensor that can find out both when a ball is near. This problem is simple and can be solved by a domain-independent contingent planner in principle, but in practice this is not possible: the size of any valid plan constructed by a contingent planner is exponential in the number of observations which in these problems is very large. This doesn’t mean that planning techniques are of no use for these problems but that building or verifying complete contingent plans is not feasible in general. In this work, we develop a domain-independent action selection mechanism that does not build full contingent plans but just chooses the action to do next in a closed-loop fashion. For this to work, however, the mechanism must be both fast and informed. We take advantage of recent ideas that allow delete and precondition-free contingent problems to be converted into conformant problems, and conformant problems into classical ones, for mapping the action selection problem in contingent planning into an action selection problem in classical planning that takes sensing actions into account. The formulation is tested over standard contingent planning benchmarks and problems that require plans of exponential size.

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References

  1. 1.
    Peot, M., Smith, D.E.: Conditional nonlinear planning. In: Hendler, J. (ed.) Proc. 1st Int. Conf. on AI Planning Systems, pp. 189–197 (1992)Google Scholar
  2. 2.
    Pryor, L., Collins, G.: Planning for contingencies: A decision-based approach. Journal of AI Research 4, 287–339 (1996)Google Scholar
  3. 3.
    Haslum, P., Jonsson, P.: Some results on the complexity of planning with incomplete information. In: Biundo, S., Fox, M. (eds.) ECP 1999. LNCS, vol. 1809, Springer, Heidelberg (1999)Google Scholar
  4. 4.
    Rintanen, J.: Complexity of planning with partial observability. In: Proc. ICAPS-2004, pp. 345–354 (2004)Google Scholar
  5. 5.
    Bonet, B., Geffner, H.: Planning with incomplete information as heuristic search in belief space. In: Proc. of AIPS-2000, pp. 52–61. AAAI Press, Stanford, California, USA (2000)Google Scholar
  6. 6.
    Hoffmann, J., Brafman, R.: Contingent planning via heuristic forward search with implicit belief states. In: Proc. ICAPS 2005 (2005)Google Scholar
  7. 7.
    Bertoli, P., Cimatti, A., Roveri, M., Traverso, P.: Strong planning under partial observability. Artif. Intell. 170(4-5), 337–384 (2006)zbMATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Bryce, D., Kambhampati, S., Smith, D.E.: Planning graph heuristics for belief space search. Journal of AI Research 26, 35–99 (2006)Google Scholar
  9. 9.
    Petrick, R., Bacchus, F.: A knowledge-based approach to planning with incomplete information and sensing. In: Proc. AIPS 2002, pp. 212–221 (2002)Google Scholar
  10. 10.
    Palacios, H., Geffner, H.: Compiling uncertainty away: Solving conformant planning problems using a classical planner (sometimes). In: Proc. AAAI 2006 (2006)Google Scholar
  11. 11.
    Bonet, B., Givan, B.: Results of the conformant track of the 5th int. planning competition (2006), at http://www.ldc.usb.ve/~bonet/ipc5/docs/results-conformant.pdf
  12. 12.
    Palacios, H., Geffner, H.: From conformant into classical planning: Efficient translations that may be complete too. In: Proc. ICAPS 2007 (2007)Google Scholar
  13. 13.
    Hoffmann, J., Nebel, B.: The FF planning system: Fast plan generation through heuristic search. Journal of Artificial Intelligence Research 14, 253–302 (2001)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Alexandre Albore
    • 1
  • Héctor Palacios
    • 1
  • Hector Geffner
    • 2
  1. 1.Universitat Pompeu Fabra, Passeig de Circumvalació 8, 08003 BarcelonaSpain
  2. 2.ICREA & Universitat Pompeu Fabra, Passeig de Circumvalació 8, 08003 BarcelonaSpain

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