State-based regression with sensing and knowledge

Richard Scherl, Cao Son Tran, Chitta Baral

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

Abstract

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 publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages345-357
Number of pages13
Volume5351 LNAI
DOIs
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)03029743
ISSN (Electronic)16113349

Other

Other10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008
CountryViet Nam
CityHanoi
Period12/15/0812/19/08

Fingerprint

Sensing
Regression
Planning
Propositional Logic
Soundness
Modal Logic
Progression
Completeness
Semantics
Formulation
Operator
Knowledge
Language

Keywords

  • Knowledge
  • Plans
  • Regression
  • Sensing

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Scherl, R., Tran, C. S., & Baral, C. (2008). State-based regression with sensing and knowledge. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5351 LNAI, pp. 345-357). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5351 LNAI). https://doi.org/10.1007/978-3-540-89197-0_33

State-based regression with sensing and knowledge. / Scherl, Richard; Tran, Cao Son; Baral, Chitta.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5351 LNAI 2008. p. 345-357 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5351 LNAI).

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

Scherl, R, Tran, CS & Baral, C 2008, State-based regression with sensing and knowledge. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 5351 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5351 LNAI, pp. 345-357, 10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008, Hanoi, Viet Nam, 12/15/08. https://doi.org/10.1007/978-3-540-89197-0_33
Scherl R, Tran CS, Baral C. State-based regression with sensing and knowledge. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5351 LNAI. 2008. p. 345-357. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-89197-0_33
Scherl, Richard ; Tran, Cao Son ; Baral, Chitta. / State-based regression with sensing and knowledge. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5351 LNAI 2008. pp. 345-357 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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