Creating Brain-Like Intelligence From Basic Principles to Complex In
This state-of-the-art-survey documents the scientific outcome of the International Symposium „Creating Brain-Like Intelligence", which took place in Hohenstein, Germany, in February 2007. It presents an introduction to this emerging interdisciplinary fiel
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Subseries of Lecture Notes in Computer Science
5436
Bernhard Sendhoff Edgar Körner Olaf Sporns Helge Ritter Kenji Doya (Eds.)
Creating Brain-Like Intelligence From Basic Principles to Complex Intelligent Systems
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Series Editors Randy Goebel, University of Alberta, Edmonton, Canada Jörg Siekmann, University of Saarland, Saarbrücken, Germany Wolfgang Wahlster, DFKI and University of Saarland, Saarbrücken, Germany Volume Editors Bernhard Sendhoff Edgar Körner Honda Research Institute Europe GmbH 63073 Offenbach/Main, Germany E-mail: {bs,edgar.koerner}@honda-ri.de Olaf Sporns Indiana University, Dept. of Psychological and Brain Sciences Bloomington, IN 47405, USA E-mail: [email protected] Helge Ritter Bielefeld University, Neuroinformatics Group 33615 Bielefeld, Germany E-mail: [email protected] Kenji Doya Okinawa Institute of Science and Technology, Neural Computation Unit Okinawa 904-2234, Japan E-mail: [email protected] The cover illustration is the work of Dr. Frank Joublin, Honda Research Institute Europe GmbH Library of Congress Control Number: Applied for CR Subject Classification (1998): I.2, F.1, I.2.10, I.4, I.5, J.3-4, H.5.2 LNCS Sublibrary: SL 7 – Artificial Intelligence ISSN ISBN-10 ISBN-13
0302-9743 3-642-00615-9 Springer Berlin Heidelberg New York 978-3-642-00615-9 Springer Berlin Heidelberg New York
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Preface
The International Symposium Creating Brain-Like Intelligence was held in February 2007 in Germany. The symposium brought together notable scientists from different backgrounds and with different expertise related to the emerging field of brain-like intelligence. Our understanding of the principles behind brain-like intelligence is still limited. After all, we have had to acknowledge that after tremendous advances in areas like neural networks, computational and artificial intelligence (a field that had just celebrated its 50 year anniversary) and fuzzy systems, we are still not able to mimic even the lower-level sensory capabilities of humans or animals. We asked what the biggest obstacles are and how we could gain ground toward a scientific understanding of the autonomy, flexibility, and robustness of intelligent biological systems as they strive to survive. New principles are u