Entropy bounds on Bayesian learning

Gossner, O.ORCID logo & Tomala, T. (2008). Entropy bounds on Bayesian learning. Journal of Mathematical Economics, 44(1), 24-32. https://doi.org/10.1016/j.jmateco.2007.04.006
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An observer of a process View the MathML source believes the process is governed by Q whereas the true law is P. We bound the expected average distance between P(xt|x1,…,xt−1) and Q(xt|x1,…,xt−1) for t=1,…,n by a function of the relative entropy between the marginals of P and Q on the n first realizations. We apply this bound to the cost of learning in sequential decision problems and to the merging of Q to P.

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