Abstract
In the Chapter, some basic concepts of Bayesian probability theory are presented, as they provide the theoretical background for subsequent work. Hereinafter, multi-objective optimisation problems will be regarded in terms of search for information: the choice of the Bayesian theoretical structure relies on its power and flexibility in treating such problems.
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References
Bretthorst, G.L. (1988), “Bayesian Spectrum Analysis and Parameter Estimation”, in Lecture Notes in Statistics, Issue 48, Springer Verlag
Ferguson, T.S. (1973), “A Bayesian Analysis of Some Non-parametric Problems”, Annals of Statistics, vol. 1, no. 2, pp. 209–230
Jaynes, E.T. (1974), Probability Theory with Applications in Science and Engineering, on-line manuscripts, http://bayes.wustl.edu/etj
Jeffreys, H. (1939), Theory of Probability, Clarendon Press
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Barba, P.D. (2010). An Introduction to Bayesian Probability Theory. In: Multiobjective Shape Design in Electricity and Magnetism. Lecture Notes in Electrical Engineering, vol 47. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3080-1_15
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DOI: https://doi.org/10.1007/978-90-481-3080-1_15
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