Reasoning and planning with sensing actions, incomplete information, and static causal laws using answer set programming

  • Authors:

  • Phan Huy Tu;Tran Cao Son;Chitta Baral

  • Affiliations:

  • Department of Computer Science, New Mexico State University, PO Box 30001, MSC CS, Las Cruces, NM 88003, USA (e-mail: tphan@cs.nmsu.edu, tson@cs.nmsu.edu);Department of Computer Science, New Mexico State University, PO Box 30001, MSC CS, Las Cruces, NM 88003, USA (e-mail: tphan@cs.nmsu.edu, tson@cs.nmsu.edu);Department of Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, USA (e-mail: chitta@asu.edu)

  • Venue:
  • Theory and Practice of Logic Programming
  • Year:
  • 2007

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Abstract

We extend the 0-approximation of sensing actions and incomplete information in Son and Baral (2001) to action theories with static causal laws and prove its soundness with respect to the possible world semantics. We also show that the conditional planning problem with respect to this approximation is NP-complete. We then present an answer set programming based conditional planner, called ASCP, that is capable of generating both conformant plans and conditional plans in the presence of sensing actions, incomplete information about the initial state, and static causal laws. We prove the correctness of our implementation and argue that our planner is sound and complete with respect to the proposed approximation. Finally, we present experimental results comparing ASCP to other planners.