Overview
- First book presenting "machine learning/agent theory/sequential decision theory" from an "algorithmic information theory" point of view
- Includes supplementary material: sn.pub/extras
Part of the book series: Texts in Theoretical Computer Science. An EATCS Series (TTCS)
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Table of contents (8 chapters)
Authors and Affiliations
About the author
Marcus Hutter received his masters in computer sciences in 1992 at the Technical University in Munich, Germany. After his PhD in theoretical particle physics he developed algorithms in a medical software company for 5 years. For four years he has been working as a researcher at the AI institute IDSIA in Lugano, Switzerland. His current interests are centered around reinforcement learning, algorithmic information theory and statistics, universal induction schemes, adaptive control theory, and related areas.
IDSIA (Istituto Dalle Molle di Studi sull'Intelligenza Artificiale) is a non-profit oriented research institute for artificial intelligence, affiliated with both the University of Lugano and SUPSI. It focusses on machine learning (artificial neural networks, reinforcement learning), optimal universal artificial intelligence and optimal rational agents, operations research, complexity theory, and robotics. In Business Week's "X-Lab Survey" IDSIA was ranked in fourth place in the category "Computer Science - Biologically Inspired", after much larger institutions. IDSIA also ranked in the top 10 of the broader category "Artificial Intelligence."
Bibliographic Information
Book Title: Universal Artificial Intelligence
Book Subtitle: Sequential Decisions Based on Algorithmic Probability
Authors: Marcus Hutter
Series Title: Texts in Theoretical Computer Science. An EATCS Series
DOI: https://doi.org/10.1007/b138233
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2005
Hardcover ISBN: 978-3-540-22139-5Published: 12 October 2004
Softcover ISBN: 978-3-642-06052-6Published: 06 November 2010
eBook ISBN: 978-3-540-26877-2Published: 29 December 2005
Series ISSN: 1862-4499
Series E-ISSN: 1862-4502
Edition Number: 1
Number of Pages: XX, 278
Topics: Artificial Intelligence, Coding and Information Theory, Theory of Computation, Mathematical Logic and Formal Languages, Probability and Statistics in Computer Science