Le-Chi Tuan ; Chitta Baral ; Tran Cao Son - A State-Based Regression Formulation for Domains with Sensing Actions<br> and Incomplete Information

lmcs:2238 - Logical Methods in Computer Science, October 2, 2006, Volume 2, Issue 4 - https://doi.org/10.2168/LMCS-2(4:2)2006
A State-Based Regression Formulation for Domains with Sensing Actions<br> and Incomplete InformationArticle

Authors: Le-Chi Tuan ; Chitta Baral ; Tran Cao Son

    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 a three-valued characterization of domains with sensing actions to define the regression function. We prove the soundness and completeness of our regression formulation with respect to the definition of progression. More specifically, we show that (i) a plan obtained through regression for a planning problem is indeed a progression solution of that planning problem, and that (ii) for each plan found through progression, using regression one obtains that plan or an equivalent one.


    Volume: Volume 2, Issue 4
    Published on: October 2, 2006
    Submitted on: January 13, 2006
    Keywords: Computer Science - Artificial Intelligence,I.2.4,I.2.8
    Funding:
      Source : OpenAIRE Graph
    • MII: Frameworks for the Development of Efficient and Scalable Knowledge-based Systems; Funder: National Science Foundation; Code: 0220590
    • Knowledge Representation, Reasoning, and Problem Solving in a Cellular Domain; Funder: National Science Foundation; Code: 0412000
    • CRI: Computing Support for the Next Generation Application-driven Declarative Programming Systems; Funder: National Science Foundation; Code: 0454066
    • CREST: Center for Research Excellence in Bioinformatics and Computational Biology; Funder: National Science Foundation; Code: 0420407
    • Reasoning and Plannning with Sensing Actions and Their Applications; Funder: National Science Foundation; Code: 0070463

    1 Document citing this article

    Consultation statistics

    This page has been seen 933 times.
    This article's PDF has been downloaded 303 times.