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

Phan Huy Tu, Tran Cao Son, Chitta Baral

Research output: Contribution to journalArticle

30 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)377-450
Number of pages74
JournalTheory and Practice of Logic Programming
Volume7
Issue number4
DOIs
StatePublished - Jul 1 2007

Keywords

  • Answer set programming
  • Conditional planning
  • Conformant planning
  • Incomplete information
  • Reasoning about actions and changes
  • Sensing actions

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics
  • Artificial Intelligence

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