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1 results

  • Bayesian dynamic programming

  • Ulrich Rieder
  • Journal:
    Advances in Applied Probability / Volume 7 / Issue 2 / June 1975
    Published online by Cambridge University Press:
    01 July 2016, pp. 330-348
    Print publication:
    June 1975

  • We consider a non-stationary Bayesian dynamic decision model with general state, action and parameter spaces. It is shown that this model can be reduced to a non-Markovian (resp. Markovian) decision model with completely known transition probabilities. Under rather weak convergence assumptions on the expected total rewards some general results are presented concerning the restriction on deterministic generalized Markov policies, the criteria of optimality and the existence of Bayes policies. These facts are based on the above transformations and on results of Hindererand Schäl.