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19952005
most citedAdaptive Online Prediction by Following the Perturbed Leader

114 citations · 157 across the 12 of their papers we have counts for

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6 papers · 1 filter

cs.AI2005114 cited

Adaptive Online Prediction by Following the Perturbed Leader

Marcus Hutter, Jan Poland

When applying aggregating strategies to Prediction with Expert Advice, the learning rate must be adaptively tuned. The natural choice of sqrt(complexity/current loss) renders the a…

cs.AI20036 cited

Universal Sequential Decisions in Unknown Environments

Marcus Hutter

We give a brief introduction to the AIXI model, which unifies and overcomes the limitations of sequential decision theory and universal Solomonoff induction. While the former theor…

cs.AI2002

Self-Optimizing and Pareto-Optimal Policies in General Environments based on Bayes-Mixtures

Marcus Hutter

The problem of making sequential decisions in unknown probabilistic environments is studied. In cycle action results in perception and reward , where all quant…

cs.AI2001

Market-Based Reinforcement Learning in Partially Observable Worlds

Ivo Kwee, Marcus Hutter, Juergen Schmidhuber

Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an…

cs.AI2001

Fitness Uniform Selection to Preserve Genetic Diversity

Marcus Hutter

In evolutionary algorithms, the fitness of a population increases with time by mutating and recombining individuals and by a biased selection of more fit individuals. The right sel…

cs.AI1999

New Error Bounds for Solomonoff Prediction

Marcus Hutter

Solomonoff sequence prediction is a scheme to predict digits of binary strings without knowing the underlying probability distribution. We call a prediction scheme informed when it…