Universal Artificial Intelligence (pilot talk)

Dr Marcus Hutter (School of Computer Science, ANU)

COMPUTER SCIENCE SEMINAR

DATE: 2009-08-26
TIME: 11:00:00 - 12:00:00
LOCATION: RSISE Seminar Room, ground floor, building 115, cnr. North and Daley Roads, ANU
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ABSTRACT:
A key property of intelligence is to learn from experience, build models of the environment from the acquired knowledge, and use these models for prediction. In philosophy this is called inductive inference, in statistics it is called estimation and prediction, and in computer science it is addressed by machine learning. The second key property of intelligence is to exploit the learned predictive model for making intelligent decisions or actions. Together, in computer science this is called reinforcement learning, in engineering it is called adaptive control, and in statistics and other fields it is called sequential decision theory. The talk will introduce the philosophical, statistical, and computational aspects of inductive inference, Solomonoff's unifying universal solution, and the theory of universal learning agents that incorporate most aspects of rational intelligence.

Reading Group: This is a pilot talk to a subsequent reading group on the same topic every Wednesday, 10am-11am, in the RSISE Building, Common LHS Room, A203.

The reading group will focus on the key ingredients to the theories of Universal Induction and Universal AI, which are important subjects in their own right: Occam's razor; Turing machines; Kolmogorov complexity; probability theory; Solomonoff induction; Bayesian sequence prediction; minimum description length principle; intelligent agents; sequential decision theory; adaptive control theory; reinforcement learning; Levin search and extensions; and others.

BIO:
Marcus Hutter is Associate Professor in the RSISE at the ANU and NICTA adjunct. He holds a PhD and BSc in physics and a Habilitation, MSc, and BSc in informatics. Since 2000, his research has centered around the information-theoretic foundations of inductive reasoning and reinforcement learning, which resulted in 50+ publications and several awards. His book "Universal Artificial Intelligence" (Springer, EATCS, 2005) develops the first sound and complete theory of AI. He also runs the Human Knowledge Compression Contest (50'000 Euro H-prize).