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A Survey of Probabilistic Models Using the Bayesian Programming Methodology as a Unifying Framework
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This paper presents a survey of the most common
probabilistic models for artefact conception. We use
a generic formalism called Bayesian Programming,
which we introduce briefly, for reviewing the main
probabilistic models found in the literature. Indeed,
we show that Bayesian Networks, Markov Localization,
Kalman filters, etc., can all be captured under this single
formalism. We believe it oers the novice reader a
good introduction to these models, while still providing
the experienced reader an enriching global view of the
field.
2003
A Survey of Probabilistic Models Using the Bayesian Programming Methodology as a Unifying Framework
Robotics
Bessiere
P
P Bessiere
Diard
J
J Diard
Mazer
E
E Mazer