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Belief extrapolation (or how to reason about observations and unpredicted change)

Dupin de Saint-Cyr, Florence; Lang, Jérôme (2011), Belief extrapolation (or how to reason about observations and unpredicted change), Artificial Intelligence, 175, 2, p. 760-790. http://dx.doi.org/10.1016/j.artint.2010.11.002

Type
Article accepté pour publication ou publié
Date
2011
Journal name
Artificial Intelligence
Volume
175
Number
2
Publisher
Elsevier
Pages
760-790
Publication identifier
Metadata
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Author(s)
Dupin de Saint-Cyr, Florence cc

Lang, Jérôme
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
We give a logical framework for reasoning with observations at different time points. We call belief extrapolation the process of completing initial belief sets stemming from observations by assuming minimal change. We give a general semantics and we propose several extrapolation operators. We study some key properties verified by these operators and we address computational issues. We study in detail the position of belief extrapolation with respect to revision and update: in particular, belief extrapolation is shown to be a specific form of time-stamped belief revision. Several related lines of work are positioned with respect to belief extrapolation.
Subjects / Keywords
Reasoning about change; Temporal reasoning; Belief change; Belief revision