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03541nam a22004455i 4500 |
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120301s2010 fr | s |||| 0|eng d |
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|a 9789491216343
|9 978-94-91216-34-3
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|a 10.2991/978-94-91216-34-3
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|a Q334-342
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|a TJ210.2-211.495
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|a 006.3
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|a Rohde, Marieke.
|e author.
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|a Enaction, Embodiment, Evolutionary Robotics
|h [electronic resource] :
|b Simulation Models for a Post-Cognitivist Science of Mind /
|c by Marieke Rohde.
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|a Paris :
|b Atlantis Press,
|c 2010.
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|a XXXIV, 242p.
|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
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|a Atlantis Thinking Machines,
|x 1877-3273 ;
|v 1
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|a Enactive Cognitive Science -- Methods and Methodology -- Linear Synergies as a Principle in Motor Control -- An Exploration of Value Systems Architectures -- Perceptual Crossing in One Dimension -- Perceptual Crossing in Two Dimensions -- The Embodiment of Time -- An Experiment on Adaptation to Tactile Delays -- Simulating the Experiment on Tactile Delays -- Perceived Simultaneity and Sensorimotor Latencies -- Outlook.
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|a This is an unusual book. It launches a new style of research into the nature of the mind, a style that pro?ciently uncovers, explores and exploits the synergies between complex systems thinking, sophisticated theoretical critique, synthetic modeling technologies and experimental work. Rather than adopting a grandiose programmatic approach, Marieke Rohde presents us with a pragmatic conjunction of elements, each of them strongly feeding off the others and making it impossible to shelf her work strictly under any one rubric such as psychology, robotics, arti?cial intelligence or philosophy of mind. Perhaps the least unjust choice is to call this a work of new cognitive science. It is yesterday’s news to remark on how our conceptual framework for understanding c- plex systems is changing. There is a recognized need to supplement the scienti?c categories of mechanistic, XIX century thought for new ways of thinking about non-linear forms of interaction and inter-relation between events and processes at multiple scales. Since the times of cybernetics and in parallel to the development of the computer as a scienti?c tool, we have witnessed several proposals for “revolutionary” ways of dealing with complexity: catastrophe theory, general systems theory, chaos, self-organized criticality, complex n- works, etc. Despite not always ful?lling their stated potential, these ideas have helped us increase our capability to understand complex systems and have in general left us with new concepts, new tools and new ways of formulating questions. This conceptual change, however, has not been homogeneous.
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|a Computer science.
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|a Artificial intelligence.
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|a Computer Science.
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|a Artificial Intelligence (incl. Robotics).
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|a SpringerLink (Online service)
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|t Springer eBooks
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|a Atlantis Thinking Machines,
|x 1877-3273 ;
|v 1
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|u http://dx.doi.org/10.2991/978-94-91216-34-3
|z Full Text via HEAL-Link
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|a ZDB-2-SCS
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|a Computer Science (Springer-11645)
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