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arxiv: 1412.3276 · v1 · pith:K5A2OPUZnew · submitted 2014-12-10 · 💻 cs.LG · stat.ML

Generalised Entropy MDPs and Minimax Regret

classification 💻 cs.LG stat.ML
keywords banditbayesianbeliefsconsiderdiscoverdiscussentropyextend
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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.

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