State-based regression with sensing and knowledge

Richard Scherl, Cao Son Tran, Chitta Baral

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


This paper develops a state-based regression method for planning domains with sensing operators and a representation of the knowledge of the planning agent. The language includes primitive actions, sensing actions, and conditional plans. We prove the soundness and completeness of the regression formulation with respect to the definition of progression and the semantics of a propositional modal logic of knowledge. It is our expectation that this work will serve as the foundation for the extension of recently successful work on state-based regression planning to include sensing and knowledge as well.

Original languageEnglish (US)
Title of host publicationPRICAI 2008
Subtitle of host publicationTrends in Artificial Intelligence - 10th Pacific Rim International Conference on Artificial Intelligence, Proceedings
Number of pages13
StatePublished - 2008
Event10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008 - Hanoi, Viet Nam
Duration: Dec 15 2008Dec 19 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5351 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008
Country/TerritoryViet Nam


  • Knowledge
  • Plans
  • Regression
  • Sensing

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'State-based regression with sensing and knowledge'. Together they form a unique fingerprint.

Cite this