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Marcus Hutter

Computer scientist

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Marcus Hutter
Nationality	German
Alma mater	Technical University Munich and Ludwig Maximilian University of Munich
Known for	Universal artificial intelligence Artificial General Intelligence
Awards	IJCAI 2023 Alignment 2018 AGI 2016 UAI 2016 IJCAI-JAIR 2014 Kurzweil AGI 2009 Lindley 2006 Best Paper Prizes
Scientific career
Fields	Artificial Intelligence Bayesian Statistics Information Theory Particle Physics
Institutions	DeepMind, Google, IDSIA, ANU, BrainLAB
Thesis	Instantons in QCD (1996)
Doctoral advisor	Harald Fritzsch
Other academic advisors	Wilfried Brauer
Doctoral students	Shane Legg and Jan Leike and Tor Lattimore
Website	www.hutter1.net

Marcus Hutter (born April 14, 1967 in Munich) is a professor and artificial intelligence researcher. As a Senior Scientist at DeepMind, he is researching the mathematical foundations of artificial general intelligence.^[1] He is on leave from his professorship at the ANU College of Engineering and Computer Science of the Australian National UniversityinCanberra, Australia.^[2] Hutter studied physics and computer science at the Technical University of Munich. In 2000 he joined Jürgen Schmidhuber's group at the Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (Dalle Molle Institute for Artificial Intelligence Research) in Manno, Switzerland.^{[citation needed]} He developed a mathematical theory of artificial general intelligence. His book Universal Artificial Intelligence: Sequential Decisions Based on Algorithmic Probability was published by Springer in 2005.^[3]

Research[edit]

Starting in 2000, Hutter developed and published a mathematical theory of artificial general intelligence, AIXI, based on idealised intelligent agents and reward-motivated reinforcement learning.^{[4][5]: 399 [6]}

In 2005, Hutter and Legg published an intelligence test for artificial intelligence devices.^[7]

In 2009, Hutter developed and published the theory of feature reinforcement learning.^[8]

In 2014, Lattimore and Hutter published an asymptotically optimal extension of the AIXI agent.^[9]

Hutter Prize[edit]

In 2006, Hutter announced the Hutter Prize for Lossless Compression of Human Knowledge, with a total of €50,000 in prize money.^[10] In 2020, Hutter raised the prize money for the Hutter Prize to €500,000.^[11][6]

See also[edit]

• Solomonoff induction

Published works[edit]

• Marcus Hutter (2002). "The Fastest and Shortest Algorithm for All Well-Defined Problems". International Journal of Foundations of Computer Science. 13 (3). World Scientific: 431–443. arXiv:cs/0206022. Bibcode:2002cs........6022H. doi:10.1142/S0129054102001199. S2CID 5496821.
• Marcus Hutter (2005). Universal Artificial Intelligence: Sequential Decisions Based on Algorithmic Probability. Springer. ISBN 9783540221395.
• Joel Veness, Kee Siong Ng, Marcus Hutter, William Uther and David Silver (2011). "A Monte-Carlo AIXI Approximation". Journal of Artificial Intelligence Research. 40. AAAI Press: 95–142. arXiv:0909.0801. doi:10.1613/jair.3125. S2CID 206618.{{cite journal}}: CS1 maint: multiple names: authors list (link)

References[edit]