The University of Edinburgh -
Division of Informatics
Forrest Hill & 80 South Bridge

MSc Thesis #9625

Title:Don'T Look Now: Credibility Vs Kalman Filters
Date: 1996
Abstract:This dissertation describes the adaptation of credibility theory, an actuarial technique, to the domain of intelligent agents. Credibility theory is used for experience rating in general insurance; here it is adapted for experience rating of an agent's estimate of the dynamism of its environment. The goal is to minimise the cost/benefit of making observations by relating the observation frequency to the dynamism of the world. The results from adapted credibility theory are compared to those achieved by a simple implementation of a Kalman filter, but the testbed does not provide conclusive results. However, the adaptation of a credibility theory is shown to be flawed, since variable weighting of the a priori data produces a performance deterioration compared to a fixed weighting between a priori and recent estimates. Various problems with the adaptation of credibility theory have been identified and further work suggested to improve the performance.

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