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Adaptivity and Learning: An Interdisciplinary Debate
 
 
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Adaptivity and Learning: An Interdisciplinary Debate [Hardcover]

Reimer Kühn (Editor), Randolf Menzel (Editor), Wolfram Menzel (Editor)

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Book Description

3540000917 978-3540000914 August 5, 2003 1
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.

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 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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Inside This Book (learn more)
First Sentence:
Learning is an elemental principle that allows the survival of living organisms in a complex environment. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
cytoplasmic phosphate concentration, unspecific reinforcement, situational uniformities, general landscape memory, own structuredness, semantic space structure, attentional map, connectionistic representation, percept structure, connectionistic systems, folding networks, linear operation mode, usage regularities, pixel appearance, external phosphate concentration, honeybee behaviour, standard feedforward network, learned odour, different descriptive levels, evaluating stimulus, computational semiotics, phosphate uptake system, phylogenetic memory, coarse grained analysis, simulation league
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, International Conference, Monte Carlo, Morgan Kaufmann, Springer Verlag, Cambridge University Press, Journal of Comparative Physiology, Oxford University Press, Academic Press, Lecture Notes, Michael Biehl, Theoretical Computer Science, Athena Scientific, John Wiley, Journal of Experimental Biology, Cereb Cortex, Support Vector Learning, Annual Review of Neuroscience, Harvard University Press, International Workshop, North Holland, Proc Natl Acad Sci, Psychological Review, Robot Soccer World Cup, Addison Wesley
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