# Generalised Entropy MDPs and Minimax Regret

arXiv: https://arxiv.org/abs/1412.3276 · HTML: https://mlsanity.com/paper/1412.3276/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Dec 2014.

## Built on by (most cited first, 1 of 1)

- [Minimax-Bayes Reinforcement Learning](https://mlsanity.com/paper/2302.10831/) (2023)

## Abstract (arXiv)

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.