Obtaining a Bayesian map for data fusion and failure detection under uncertainty

Authors:
F. Aznar;M. Pujol;R. Rizo
Affiliations:
Department of Computer Science and Artificial Intelligence, University of Alicante;Department of Computer Science and Artificial Intelligence, University of Alicante;Department of Computer Science and Artificial Intelligence, University of Alicante
Venue:
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Year:
2005

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Abstract

This paper presents a generic Bayesian map and shows how it is used for the development of a task done by an agent arranged in an environment with uncertainty. This agent interacts with the world and is able to detect, using only readings from its sensors, any failure of its sensorial system. It can even continue to function properly while discarding readings obtained by the erroneous sensor/s. A formal model based on Bayesian Maps is proposed. The Bayesian Maps brings up a formalism where implicitly, using probabilities, we work with uncertainly. Some experimental data is provided to validate the correctness of this approach.