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

Published online by Cambridge University Press:  01 July 2007

PHAN HUY TU ,
TRAN CAO SON  and
CHITTA BARAL
PHAN HUY TU
Affiliation:
Department of Computer Science, New Mexico State University, PO Box 30001, MSC CS, Las Cruces, NM 88003, USA (e-mail: [email protected], [email protected])
TRAN CAO SON
Affiliation:
Department of Computer Science, New Mexico State University, PO Box 30001, MSC CS, Las Cruces, NM 88003, USA (e-mail: [email protected], [email protected])
CHITTA BARAL
Affiliation:
Department of Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, USA (e-mail: [email protected])
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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.

Keywords

Reasoning about actions and changessensing actionsincomplete informationconformant planningconditional planninganswer set programming
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 7 , Issue 4 , July 2007 , pp. 377 - 450
Copyright
Copyright © Cambridge University Press 2007

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