Regression with respect to sensing actions and partial states

Le Chi Tuan, Chitta Baral, Xin Zhang, Tran Cao Son

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper, we present a state-based regression function for planning domains where an agent does not have complete information and may have sensing actions. We consider binary domains ', and employ the 0-approximation (Son & Baral 2001) to define the regression function. In binary domains, the use of 0-approximation means using 3-valued states. Although planning using this approach is incomplete with respect to the full semantics, we adopt it to have a lower complexity. We prove the soundness and completeness of our regression formulation with respect to the definition of progression and develop a conditional planner that utilizes our regression function.

Original languageEnglish (US)
Title of host publicationProceedings of the National Conference on Artificial Intelligence
Pages556-561
Number of pages6
StatePublished - 2004
EventProceedings - Nineteenth National Conference on Artificial Intelligence (AAAI-2004): Sixteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2004) - San Jose, CA, United States
Duration: Jul 25 2004Jul 29 2004

Other

OtherProceedings - Nineteenth National Conference on Artificial Intelligence (AAAI-2004): Sixteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2004)
CountryUnited States
CitySan Jose, CA
Period7/25/047/29/04

ASJC Scopus subject areas

  • Software

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  • Cite this

    Tuan, L. C., Baral, C., Zhang, X., & Son, T. C. (2004). Regression with respect to sensing actions and partial states. In Proceedings of the National Conference on Artificial Intelligence (pp. 556-561)