© 2009

Creating Brain-Like Intelligence

From Basic Principles to Complex Intelligent Systems

  • Bernhard Sendhoff
  • Edgar Körner
  • Olaf Sporns
  • Helge Ritter
  • Kenji Doya

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5436)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 5436)

Table of contents

  1. Front Matter
  2. Bernhard Sendhoff, Edgar Körner, Olaf Sporns
    Pages 1-14
  3. Gustavo Deco, Edmund T. Rolls
    Pages 31-50
  4. Helge Ritter, Robert Haschke, Jochen J. Steil
    Pages 84-102
  5. Britta Wrede, Katharina J. Rohlfing, Marc Hanheide, Gerhard Sagerer
    Pages 139-150
  6. Sethu Vijayakumar, Marc Toussaint, Giorgios Petkos, Matthew Howard
    Pages 151-191
  7. Christian Goerick
    Pages 192-214
  8. Julian Eggert, Heiko Wersing
    Pages 215-247
  9. Stefan Elfwing, Eiji Uchibe, Kenji Doya
    Pages 278-302
  10. Mototaka Suzuki, Tommaso Gritti, Dario Floreano
    Pages 303-313
  11. Christoph S. Herrmann, Frank W. Ohl
    Pages 314-327
  12. Hiroshi Tsujino, Johane Takeuchi, Osamu Shouno
    Pages 328-350
  13. Back Matter

About this book


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 field by drawing together 15 articles from researchers across a broad range of disciplines.

Brain-Like intelligence attempts a representation of the environment including the system itself. It has to cope with a continuous influx of an immense amount of mostly unspecific information and cannot be identified with a singular functionality. It is the versatility of brain-like intelligence, its robustness and plasticity which makes it the object of our quest.

After 50 years of artificial intelligence research however, we are still not able to mimic even the lower level sensory capabilities of animals. But we are beginning to move in the right direction by identifying the biggest obstacles and starting to understand the autonomy, flexibility, and robustness of intelligent biological systems. This collection of articles is evidence of this progress and represents the current state of art in several research fields that are embraced by brain-like intelligence.



artificial intelligence autonom brain-body-environment clustering cognitive vision system computer vision context sensing decision making embodied evolution emotion recognition human sensing intelligence intelligent systems tar user experience

Editors and affiliations

  • Bernhard Sendhoff
    • 1
  • Edgar Körner
    • 2
  • Olaf Sporns
    • 3
  • Helge Ritter
    • 4
  • Kenji Doya
    • 5
  1. 1.Honda Research Institute Europe GmbH, 63073 Offenbach/MainGermany
  2. 2.Honda Research Institute Europe GmbH, Carl-Legien-Strasse 30, 63073, Offenbach/MainGermany
  3. 3.Dept. of Psychological and Brain SciencesIndiana UniversityBloomingtonUSA
  4. 4.Faculty of Technology, Neuroinformatics GroupBielefeld UniversityBielefeldGermany
  5. 5.Okinawa Institute of Science and Technology, Neural Computation Unit,OkinawaJapan

Bibliographic information

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