@inproceedings{5f9a2a14c8cf4c11ad245b2b2a171a11,
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.",
author = "Kinzang Chhogyal and Abhaya Nayak and Rolf Schwitter and Abdul Sattar",
year = "2014",
doi = "10.1007/978-3-319-13560-1_55",
language = "English",
isbn = "9783319135595",
volume = "8862",
series = "Lecture Notes in Artificial Intelligence",
publisher = "Springer, Springer Nature",
pages = "694--707",
editor = "Duc-Nghia Pham and Seong-Bae Park",
booktitle = "PRICAI 2014: Trends in Artificial Intelligence",
address = "United States",
edition = "1st",
}