Entropy bounds on Bayesian learning

Article dans une revue: 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.

Auteur(s)

Olivier Gossner, Tristan Tomala

Revue
  • Journal of Mathematical Economics
Date de publication
  • 2008
Mots-clés JEL
A1 B10 C1
Mots-clés
  • Bayesian learning
  • Repeated decision problem
  • Value of information
  • Entropy
Pages
  • 24-32
Version
  • 1
Volume
  • 44