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Computer Science > Artificial Intelligence

arXiv:cs/0605017 (cs)
[Submitted on 4 May 2006]

Title: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
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Abstract: We extend the 0-approximation of sensing actions and incomplete information in [Son and Baral 2000] 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.
Comments: 72 pages, 3 figures, a preliminary version of this paper appeared in the proceedings of the 7th International Conference on Logic Programming and Non-Monotonic Reasoning, 2004. To appear in Theory and Practice of Logic Programming
Subjects: Artificial Intelligence (cs.AI)
ACM classes: I.2.3; I.2.4; I.2.8
Cite as: arXiv:cs/0605017 [cs.AI]
  (or arXiv:cs/0605017v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.cs/0605017

Submission history

From: Tran Cao Son [view email]
[v1] Thu, 4 May 2006 22:35:12 UTC (136 KB)
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