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Adaptivity And Learning An Interdisciplinary Debate 1st Edition Reimer Khn

  • SKU: BELL-4229702
Adaptivity And Learning An Interdisciplinary Debate 1st Edition Reimer Khn
$ 31.00 $ 45.00 (-31%)

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Publisher: Springer-Verlag Berlin Heidelberg
File Extension: PDF
File size: 11.03 MB
Pages: 403
Author: Reimer Kühn, Randolf Menzel, Wolfram Menzel, Ulrich Ratsch, Michael M. Richter (auth.), Reimer Kühn, Randolf Menzel, Wolfram Menzel, Ulrich Ratsch, Michael M. Richter, Ion-Olimpiu Stamatescu (eds.)
ISBN: 9783642055102, 9783662055946, 3642055109, 3662055945
Language: English
Year: 2003
Edition: 1

Product desciption

Adaptivity And Learning An Interdisciplinary Debate 1st Edition Reimer Khn by Reimer Kühn, Randolf Menzel, Wolfram Menzel, Ulrich Ratsch, Michael M. Richter (auth.), Reimer Kühn, Randolf Menzel, Wolfram Menzel, Ulrich Ratsch, Michael M. Richter, Ion-olimpiu Stamatescu (eds.) 9783642055102, 9783662055946, 3642055109, 3662055945 instant download after payment.

Adaptivity and learning have in recent decades become a common concern of scientific disciplines. These issues have arisen in mathematics, physics, biology, informatics, economics, and other fields more or less simultaneously. The aim of this publication is the interdisciplinary discourse on the phenomenon of learning and adaptivity. Different perspectives are presented and compared to find fruitful concepts for the disciplines involved. The authors select problems showing representative traits concerning the frame up, the methods and the achievements rather than to present extended overviews.

To foster interdisciplinary dialogue, this book presents diverse perspectives from various scientific fields, including:

- The biological perspective: e.g., physiology, behaviour;

- The mathematical perspective: e.g., algorithmic and stochastic learning;

- The physics perspective: e.g., learning for artificial neural networks;

- The "learning by experience" perspective: reinforcement learning, social learning, artificial life;

- The cognitive perspective: e.g., deductive/inductive procedures, learning and language learning as a high level cognitive process;

- The application perspective: e.g., robotics, control, knowledge engineering.

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