Speaker: Marcus Hutter

Marcus Hutter (born 1967) is a German computer scientist and professor at the Australian National University. Hutter was born and educated in Munich, where he studied physics and computer science at the Technical University of Munich. In 2000 he joined Jürgen Schmidhuber’s group at the Swiss Artificial Intelligence lab IDSIA, where he developed the first mathematical theory of optimal Universal Artificial Intelligence, based on Kolmogorov complexity and Ray Solomonoff’s theory of universal inductive inference. In 2006 he also accepted a professorship at the Australian National University in Canberra.

Hutter’s notion of universal AI describes the optimal strategy of an agent that wants to maximize its future expected reward in some unknown dynamic environment, up to some fixed future horizon. This is the general reinforcement learning problem. Solomonoff/Hutter’s only assumption is that the reactions of the environment in response to the agent’s actions follow some unknown but computable probability distribution.

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