Generalised Entropy MDPs and Minimax Regret
  Bayesian methods suffer from the problem of how to specify prior beliefs. One interesting idea is to consider worst-case priors. This requires solving a stochastic zero-sum game. In this paper, we extend well-known results from bandit theory in order to discover minimax-Bayes policies and discuss when they are practical. 
Emmanouil G. Androulakis, Christos Dimitrakakis
cs.LG stat.ML