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

Authors:
Florence Dupin de Saint-Cyr;Jérôme Lang
Affiliations:
IRIT, Université Paul Sabatier, 31062 Toulouse Cedex 9, France;LAMSADE, Université Paris-Dauphine, 75775 Paris Cedex 16, France
Venue:
Artificial Intelligence
Year:
2011

Citing 16
Cited 6

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Abstract

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.