Entropy bounds on Bayesian learning
Journal article: 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.
Author(s)
Olivier Gossner, Tristan Tomala
Journal
- Journal of Mathematical Economics
Date of publication
- 2008
Keywords JEL
Keywords
- Bayesian learning
- Repeated decision problem
- Value of information
- Entropy
Pages
- 24-32
URL of the HAL notice
Version
- 1
Volume
- 44