398 citations · 1.8k across the 163 of their papers we have counts for
7 papers · 1 filter
Compress and Control
Joel Veness, Marc G. Bellemare, Marcus Hutter +2
This paper describes a new information-theoretic policy evaluation technique for reinforcement learning. This technique converts any compression or density model into a correspondi…
Asymptotics of Continuous Bayes for Non-i.i.d. Sources
Tor Lattimore, Marcus Hutter
Clarke and Barron analysed the relative entropy between an i.i.d. source and a Bayesian mixture over a continuous class containing that source. In this paper a comparable result is…
Indefinitely Oscillating Martingales
Jan Leike, Marcus Hutter
We construct a class of nonnegative martingale processes that oscillate indefinitely with high probability. For these processes, we state a uniform rate of the number of oscillatio…
Robust Feature Selection by Mutual Information Distributions
Marco Zaffalon, Marcus Hutter
Mutual information is widely used in artificial intelligence, in a descriptive way, to measure the stochastic dependence of discrete random variables. In order to address questions…
Extreme State Aggregation Beyond MDPs
Marcus Hutter
We consider a Reinforcement Learning setup where an agent interacts with an environment in observation-reward-action cycles without any (esp.\ MDP) assumptions on the environment.…
Offline to Online Conversion
Marcus Hutter
We consider the problem of converting offline estimators into an online predictor or estimator with small extra regret. Formally this is the problem of merging a collection of prob…