Generalised Entropy MDPs and Minimax Regret

Emmanouil G. Androulakis; Christos Dimitrakakis

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arXiv · 1412.3276

Generalised Entropy MDPs and Minimax Regret

Emmanouil G. Androulakis·Christos Dimitrakakis

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Abstract

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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Emmanouil G. Androulakis, Christos Dimitrakakis. 2014-12-10. Generalised Entropy MDPs and Minimax Regret. https://arxiv.org/abs/1412.3276

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