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|a 9783319225999
|9 978-3-319-22599-9
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|a 10.1007/978-3-319-22599-9
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|a 006.3
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|a Anticipation Across Disciplines
|h [electronic resource] /
|c edited by Mihai Nadin.
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|a 1st ed. 2016.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2016.
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|a VII, 403 p. 105 illus., 43 illus. in color.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|a text file
|b PDF
|2 rda
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|a Cognitive Systems Monographs,
|x 1867-4925 ;
|v 29
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|a Part I Theoretical and General Aspects of Anticipation -- Part II Anticipation in Biological and Physiological Systems -- Part III Anticipation in Neural Networks -- Part IV Anticipation in Engineering and Information Technology -- Part V Anticipation, Culture, and Society.
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|a Never before was anticipation more relevant to the life and activity of humankind than it is today. “It is no overstatement to suggest that humanity’s future will be shaped by its capacity to anticipate….” (Research Agenda for the 21st Century, National Science Foundation). The sciences and the humanities can no longer risk explaining away the complexity and interactivity that lie at the foundation of life and living. The perspective of the world that anticipation opens justifies the descriptor “the post-Cartesian Revolution.” If anticipation is a valid research domain, what practical relevance can we await? Indeed, anticipation is more than just the latest catch-word in marketing the apps developed by the digital technology industry. Due to spectacular advances in the study of the living, anticipation can claim a legitimate place in current investigations and applications in the sciences and the humanities. Biology, genetics, medicine, as well as politics and cognitive, behavioral, and social sciences, provide rich evidence of anticipatory processes at work. Readers seeking a foundation for anticipation will find in these pages recent outcomes pertinent to plant life, political anticipation, cognitive science, architecture, computation. The authors contributing to this volume frame experimental data in language that can be shared among experts from all fields of endeavor. The major characteristic is the inference from the richness of data to principles and practical consequences. .
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|a Engineering.
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|a Artificial intelligence.
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|a Neural networks (Computer science).
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|a Computational intelligence.
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|a Engineering.
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|a Computational Intelligence.
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|a Mathematical Models of Cognitive Processes and Neural Networks.
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|a Artificial Intelligence (incl. Robotics).
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|a Nadin, Mihai.
|e editor.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783319225982
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| 830 |
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|a Cognitive Systems Monographs,
|x 1867-4925 ;
|v 29
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| 856 |
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|u http://dx.doi.org/10.1007/978-3-319-22599-9
|z Full Text via HEAL-Link
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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