Probabilistic belief revision via imaging

Kinzang Chhogyal; Abhaya Nayak; Rolf Schwitter; Abdul Sattar

doi:10.1007/978-3-319-13560-1_55

Probabilistic belief revision via imaging

Kinzang Chhogyal^*, Abhaya Nayak, Rolf Schwitter, Abdul Sattar

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

6 Citations (Scopus)

Abstract

While Bayesian conditioning fits in nicely with probabilistic belief expansion, its use is problematic in the context of non-trivial belief revision. Lewis’ use of imaging based on closeness between possible worlds offers a way to overcome this limitation in the context of belief update (in a dynamic environment). In this paper, we explore the use of imaging as a means to construct probabilistic belief revision. Specifically, we present explicit constructions of three candidates strategies, dubbed Naive, Gullible and Cunning, that are based on imaging, and investigate their properties.

Original language	English
Title of host publication	PRICAI 2014: Trends in Artificial Intelligence
Subtitle of host publication	13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014, Gold Coast, QLD, Australia, December 1-5, 2014, Proceedings
Editors	Duc-Nghia Pham, Seong-Bae Park
Place of Publication	Cham
Publisher	Springer, Springer Nature
Pages	694-707
Number of pages	14
Volume	8862
Edition	1st
ISBN (Electronic)	9783319135601
ISBN (Print)	9783319135595
DOIs	https://doi.org/10.1007/978-3-319-13560-1_55
Publication status	Published - 2014
Event	13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014 - Gold Coast, QLD, Australia Duration: 1 Dec 2014 → 5 Dec 2014

Publication series

Name	Lecture Notes in Artificial Intelligence
Publisher	SPRINGER-VERLAG BERLIN
Volume	8862
ISSN (Print)	0302-9743

Conference

Conference	13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014
Country	Australia
City	Gold Coast, QLD
Period	1/12/14 → 5/12/14

Access to Document

10.1007/978-3-319-13560-1_55

Link to publication in Scopus

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Chhogyal, K., Nayak, A., Schwitter, R., & Sattar, A. (2014). Probabilistic belief revision via imaging. In D-N. Pham, & S-B. Park (Eds.), PRICAI 2014: Trends in Artificial Intelligence: 13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014, Gold Coast, QLD, Australia, December 1-5, 2014, Proceedings (1st ed., Vol. 8862, pp. 694-707). (Lecture Notes in Artificial Intelligence; Vol. 8862). Cham: Springer, Springer Nature. https://doi.org/10.1007/978-3-319-13560-1_55

Chhogyal, Kinzang ; Nayak, Abhaya ; Schwitter, Rolf ; Sattar, Abdul. / Probabilistic belief revision via imaging. PRICAI 2014: Trends in Artificial Intelligence: 13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014, Gold Coast, QLD, Australia, December 1-5, 2014, Proceedings. editor / Duc-Nghia Pham ; Seong-Bae Park. Vol. 8862 1st. ed. Cham : Springer, Springer Nature, 2014. pp. 694-707 (Lecture Notes in Artificial Intelligence).

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title = "Probabilistic belief revision via imaging",

abstract = "While Bayesian conditioning fits in nicely with probabilistic belief expansion, its use is problematic in the context of non-trivial belief revision. Lewis’ use of imaging based on closeness between possible worlds offers a way to overcome this limitation in the context of belief update (in a dynamic environment). In this paper, we explore the use of imaging as a means to construct probabilistic belief revision. Specifically, we present explicit constructions of three candidates strategies, dubbed Naive, Gullible and Cunning, that are based on imaging, and investigate their properties.",

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Chhogyal, K, Nayak, A , Schwitter, R & Sattar, A 2014, Probabilistic belief revision via imaging. in D-N Pham & S-B Park (eds), PRICAI 2014: Trends in Artificial Intelligence: 13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014, Gold Coast, QLD, Australia, December 1-5, 2014, Proceedings. 1st edn, vol. 8862, Lecture Notes in Artificial Intelligence, vol. 8862, Springer, Springer Nature, Cham, pp. 694-707, 13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014, Gold Coast, QLD, Australia, 1/12/14. https://doi.org/10.1007/978-3-319-13560-1_55

Probabilistic belief revision via imaging. / Chhogyal, Kinzang; Nayak, Abhaya ; Schwitter, Rolf; Sattar, Abdul.

PRICAI 2014: Trends in Artificial Intelligence: 13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014, Gold Coast, QLD, Australia, December 1-5, 2014, Proceedings. ed. / Duc-Nghia Pham; Seong-Bae Park. Vol. 8862 1st. ed. Cham : Springer, Springer Nature, 2014. p. 694-707 (Lecture Notes in Artificial Intelligence; Vol. 8862).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

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AU - Schwitter, Rolf

AU - Sattar, Abdul

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N2 - While Bayesian conditioning fits in nicely with probabilistic belief expansion, its use is problematic in the context of non-trivial belief revision. Lewis’ use of imaging based on closeness between possible worlds offers a way to overcome this limitation in the context of belief update (in a dynamic environment). In this paper, we explore the use of imaging as a means to construct probabilistic belief revision. Specifically, we present explicit constructions of three candidates strategies, dubbed Naive, Gullible and Cunning, that are based on imaging, and investigate their properties.

AB - While Bayesian conditioning fits in nicely with probabilistic belief expansion, its use is problematic in the context of non-trivial belief revision. Lewis’ use of imaging based on closeness between possible worlds offers a way to overcome this limitation in the context of belief update (in a dynamic environment). In this paper, we explore the use of imaging as a means to construct probabilistic belief revision. Specifically, we present explicit constructions of three candidates strategies, dubbed Naive, Gullible and Cunning, that are based on imaging, and investigate their properties.

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Chhogyal K, Nayak A , Schwitter R, Sattar A. Probabilistic belief revision via imaging. In Pham D-N, Park S-B, editors, PRICAI 2014: Trends in Artificial Intelligence: 13th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2014, Gold Coast, QLD, Australia, December 1-5, 2014, Proceedings. 1st ed. Vol. 8862. Cham: Springer, Springer Nature. 2014. p. 694-707. (Lecture Notes in Artificial Intelligence). https://doi.org/10.1007/978-3-319-13560-1_55