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04039nam a22005895i 4500 |
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978-1-84628-234-8 |
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DE-He213 |
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20151204154256.0 |
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cr nn 008mamaa |
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100301s2005 xxk| s |||| 0|eng d |
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|a 9781846282348
|9 978-1-84628-234-8
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|a 10.1007/1-84628-234-9
|2 doi
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|d GrThAP
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|a Q334-342
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|a TJ210.2-211.495
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|a UYQ
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|a COM004000
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|a 006.3
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|a Konar, Amit.
|e author.
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|a Cognitive Engineering
|h [electronic resource] :
|b A Distributed Approach to Machine Intelligence /
|c by Amit Konar, Lakhmi Jain.
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|a London :
|b Springer London,
|c 2005.
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| 300 |
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|a XVIII, 354 p. 124 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Advanced Information and Knowledge Processing
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|a The Psychological Basis of Cognitive Modeling -- Parallel and Distributed Logic Programming -- Distributed Reasoning by Fuzzy Petri Nets: A Review -- Belief Propagation and Belief Revision Models in Fuzzy Petri Nets -- Building Expert Systems Using Fuzzy Petri Nets -- Distributed Learning Using Fuzzy Cognitive Maps -- Unsupervised Learning by Fuzzy Petri Nets -- Supervised Learning by a Fuzzy Petri Net -- Distributed Modeling of Abduction, Reciprocity, and Duality by Fuzzy Petri Nets -- Human Mood Detection and Control: A Cybernetic Approach -- Distributed Planning and Multi-agent Coordination of Robots.
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|a Cognitive Engineering: A Distributed Approach to Machine Intelligence explores the design issues of intelligent engineering systems. Beginning with the foundations of psychological modeling of the human mind, the main emphasis is given to parallel and distributed realization of intelligent models for application in reasoning, learning, planning and multi-agent co-ordination problems. The last two chapters provide case studies on human-mood detection and control, and behavioral co-operation of mobile robots. This is the first comprehensive text of its kind, bridging the gap between Cognitive Science and Cognitive Systems Engineering. Each chapter includes plenty of numerical examples and exercises with sufficient hints, so that the reader can solve the exercises on their own. Computer simulations are also included in most chapters to give a clear idea about the application of the algorithms undertaken in the book. In addition, mathematical analysis on convergence and stability of the neuro-fuzzy models will enable the reader to pursue their research career in cognitive engineering. Cognitive Engineering: A Distributed Approach to Machine Intelligence is unique in its theme and contents, and includes a Foreword by Professor Witold Pedrycz - written with graduates in mind, this book would also be a valuable resource for researchers in the fields of Cognitive Science, Computer Science and Cognitive Engineering.
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|a Computer science.
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|a Algorithms.
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|a Computer science
|x Mathematics.
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|a Computers.
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|a Artificial intelligence.
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|a Computer simulation.
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|a Electrical engineering.
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|a Computer Science.
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| 650 |
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|a Artificial Intelligence (incl. Robotics).
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| 650 |
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|a Communications Engineering, Networks.
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| 650 |
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4 |
|a Simulation and Modeling.
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| 650 |
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|a Symbolic and Algebraic Manipulation.
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| 650 |
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|a Algorithm Analysis and Problem Complexity.
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| 650 |
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|a Models and Principles.
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| 700 |
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|a Jain, Lakhmi.
|e author.
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| 710 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer eBooks
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| 776 |
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|i Printed edition:
|z 9781852339753
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| 830 |
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|a Advanced Information and Knowledge Processing
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| 856 |
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|u http://dx.doi.org/10.1007/1-84628-234-9
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-SCS
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| 950 |
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|a Computer Science (Springer-11645)
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