The Resource Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 1013 January 2010, editors, Paolo Grigolini, Bruce J. West
Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 1013 January 2010, editors, Paolo Grigolini, Bruce J. West
Resource Information
The item Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 1013 January 2010, editors, Paolo Grigolini, Bruce J. West represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of MissouriSt. Louis Libraries.This item is available to borrow from 1 library branch.
Resource Information
The item Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 1013 January 2010, editors, Paolo Grigolini, Bruce J. West represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of MissouriSt. Louis Libraries.
This item is available to borrow from 1 library branch.
 Summary
 This invaluable book captures the proceedings of a workshop that brought together a group of distinguished scientists from a variety of disciplines to discuss how networking influences decision making. The individual lectures interconnect psychological testing, the modeling of neuron networks and brain dynamics to the transport of information within and between complex networks. Of particular importance was the introduction of a new principle that governs how complex networks talk to one another  the Principle of Complexity Management (PCM). PCM establishes that the transfer of information fr
 Language
 eng
 Extent
 1 online resource (ix, 196 pages)
 Contents

 Preface; CONTENTS; 1. Overview of ARO program on network science for human decision making B.J. West; 1. Introduction; 2. Background; 2.1. What we know about networks; 2.2. What we do not know about the linking of physical and human networks; 3. What We Have Been Doing; 3.1. Complexity theory and modeling without scales; 3.2. Information propagation in complex adaptive networks; 4. Preliminary Conclusions; References; 2. Viewing the extended mind hypothesis (Clark & Chambers) in terms of complex systems dynamics G. Werner; 1. Background; 2. On the Extended Mind Hypothesis
 3. Brain and World as ONE Complex Dynamical System4. Praxis Ahead of Theory; 5. Conclusion; References; 3. Uncertainty in psychophysics: Deriving a network of psychophysical equations K.H. Norwich; 1. Introduction; 2. Philosophical Underpinnings; 3. Mathematical Representation of the Psychophysical Law (WeberFechner and Stevens); 4. A Network of Equations Issuing from the Entropic Form of the Psychophysical Law; 4.1. The differential threshold (DH from Fechner's conjecture) and Weber's fraction; 4.2. The hyperbolic law governing the magnitude of n (DH from Miller's magical number)
 4.3. Simple reaction time (DH is the minimum quantity of information needed to react)5. Searching for Support within Thermodynamics and Statistical Physics; 5.1. Emergence of the WeberFechner law from thermodynamics; 6. Discussion; 6.1. Review; 6.2. Quantum Sufficiat; Acknowledgements; References; 4. The collective brain E. Tagliazucchi and D.R. Chialvo; 1. Introduction; 2. Emergent Complex Dynamics is always Critical; 3. The Collective Largescale Brain Dynamics; 4. Neuronal Avalanching in Small Scale is Critical; 5. Psychophysics and Behavior; 6. An Evolutionary Perspective
 7. Noise or Critical Fluctuations? Equilibrium vs Nonequilibrium8. Outlook; Acknowledgements; References; 5. Acquiring longrange memory through adaptive avalanches S. Boettcher; 1. Introduction; 2. Motivation from Selforganized Criticality; 3. Spin Glass Ground States with Extremal Optimization; 4. EO Dynamics; 5. Annealed Optimization Model; 6. Evolution Equations for Local Search Heuristics; 6.1. Extremal optimization algorithm; 6.2. Update probabilities for extremal optimization; 6.3. Update probabilities for metropolis algorithms; 6.4. Evolution equations for a simple barrier model
 6.5. Jamming model for EOReferences; 6. Random walk of complex networks: From infinitely slow to instantaneous transition to equilibrium N.W. Hollingshad, P. Grigolini and P. Allegrini; 1. Introduction; 2. Preliminary Remarks on the Size of a Complex Network; 3. On the Master Matrix A; 4. Transition to Equilibrium in Hierarchical Networks; 5. Return to the Origin in a Scalefree Network; 5.1. Ad hoc scalefree network; 5.2. Hierarchical network; 6. Conclusions; Acknowledgements; References; 7. Coherence and complexity M. Bologna, E. Geneston, P. Grigolini, M. Turalska and M. Lukovic
 Isbn
 9789814365826
 Label
 Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 1013 January 2010
 Title
 Decision making
 Title remainder
 a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 1013 January 2010
 Statement of responsibility
 editors, Paolo Grigolini, Bruce J. West
 Subject

 Psychophysics  Congresses
 Chaotic behavior in systems
 Chaotic behavior in systems  Congresses
 Complexity (Philosophy)
 Complexity (Philosophy)  Congresses
 Conference papers and proceedings
 Congress
 Decision Making
 Decision making  Physiological aspects
 Decision making  Physiological aspects  Congresses
 MEDICAL  Neuroscience
 Neural Networks, Computer
 Neural networks (Neurobiology)
 Neural networks (Neurobiology)  Congresses
 PSYCHOLOGY  Neuropsychology
 Psychophysics
 Psychophysics
 Language
 eng
 Summary
 This invaluable book captures the proceedings of a workshop that brought together a group of distinguished scientists from a variety of disciplines to discuss how networking influences decision making. The individual lectures interconnect psychological testing, the modeling of neuron networks and brain dynamics to the transport of information within and between complex networks. Of particular importance was the introduction of a new principle that governs how complex networks talk to one another  the Principle of Complexity Management (PCM). PCM establishes that the transfer of information fr
 Cataloging source
 N$T
 Dewey number
 612.8
 Illustrations
 illustrations
 Index
 no index present
 LC call number
 QP363.3
 LC item number
 .D43 2011eb
 Literary form
 non fiction
 Nature of contents

 dictionaries
 bibliography
 NLM call number

 2011 L179
 BF 448
 http://library.link/vocab/relatedWorkOrContributorName

 Grigolini, Paolo
 West, Bruce J
 Series statement
 Studies of nonlinear phenomena in life science
 Series volume
 v. 15
 http://library.link/vocab/subjectName

 Neural networks (Neurobiology)
 Psychophysics
 Chaotic behavior in systems
 Complexity (Philosophy)
 Decision making
 Decision Making
 Neural Networks, Computer
 Psychophysics
 MEDICAL
 PSYCHOLOGY
 Chaotic behavior in systems
 Complexity (Philosophy)
 Decision making
 Neural networks (Neurobiology)
 Psychophysics
 Label
 Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 1013 January 2010, editors, Paolo Grigolini, Bruce J. West
 Antecedent source
 unknown
 Bibliography note
 Includes bibliographical references
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 multicolored
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents

 Preface; CONTENTS; 1. Overview of ARO program on network science for human decision making B.J. West; 1. Introduction; 2. Background; 2.1. What we know about networks; 2.2. What we do not know about the linking of physical and human networks; 3. What We Have Been Doing; 3.1. Complexity theory and modeling without scales; 3.2. Information propagation in complex adaptive networks; 4. Preliminary Conclusions; References; 2. Viewing the extended mind hypothesis (Clark & Chambers) in terms of complex systems dynamics G. Werner; 1. Background; 2. On the Extended Mind Hypothesis
 3. Brain and World as ONE Complex Dynamical System4. Praxis Ahead of Theory; 5. Conclusion; References; 3. Uncertainty in psychophysics: Deriving a network of psychophysical equations K.H. Norwich; 1. Introduction; 2. Philosophical Underpinnings; 3. Mathematical Representation of the Psychophysical Law (WeberFechner and Stevens); 4. A Network of Equations Issuing from the Entropic Form of the Psychophysical Law; 4.1. The differential threshold (DH from Fechner's conjecture) and Weber's fraction; 4.2. The hyperbolic law governing the magnitude of n (DH from Miller's magical number)
 4.3. Simple reaction time (DH is the minimum quantity of information needed to react)5. Searching for Support within Thermodynamics and Statistical Physics; 5.1. Emergence of the WeberFechner law from thermodynamics; 6. Discussion; 6.1. Review; 6.2. Quantum Sufficiat; Acknowledgements; References; 4. The collective brain E. Tagliazucchi and D.R. Chialvo; 1. Introduction; 2. Emergent Complex Dynamics is always Critical; 3. The Collective Largescale Brain Dynamics; 4. Neuronal Avalanching in Small Scale is Critical; 5. Psychophysics and Behavior; 6. An Evolutionary Perspective
 7. Noise or Critical Fluctuations? Equilibrium vs Nonequilibrium8. Outlook; Acknowledgements; References; 5. Acquiring longrange memory through adaptive avalanches S. Boettcher; 1. Introduction; 2. Motivation from Selforganized Criticality; 3. Spin Glass Ground States with Extremal Optimization; 4. EO Dynamics; 5. Annealed Optimization Model; 6. Evolution Equations for Local Search Heuristics; 6.1. Extremal optimization algorithm; 6.2. Update probabilities for extremal optimization; 6.3. Update probabilities for metropolis algorithms; 6.4. Evolution equations for a simple barrier model
 6.5. Jamming model for EOReferences; 6. Random walk of complex networks: From infinitely slow to instantaneous transition to equilibrium N.W. Hollingshad, P. Grigolini and P. Allegrini; 1. Introduction; 2. Preliminary Remarks on the Size of a Complex Network; 3. On the Master Matrix A; 4. Transition to Equilibrium in Hierarchical Networks; 5. Return to the Origin in a Scalefree Network; 5.1. Ad hoc scalefree network; 5.2. Hierarchical network; 6. Conclusions; Acknowledgements; References; 7. Coherence and complexity M. Bologna, E. Geneston, P. Grigolini, M. Turalska and M. Lukovic
 Control code
 777561001
 Dimensions
 unknown
 Extent
 1 online resource (ix, 196 pages)
 File format
 unknown
 Form of item
 online
 Isbn
 9789814365826
 Level of compression
 unknown
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other physical details
 illustrations
 Quality assurance targets
 not applicable
 Reformatting quality
 unknown
 Sound
 unknown sound
 Specific material designation
 remote
 System control number
 (OCoLC)777561001
 Label
 Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 1013 January 2010, editors, Paolo Grigolini, Bruce J. West
 Antecedent source
 unknown
 Bibliography note
 Includes bibliographical references
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 multicolored
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents

 Preface; CONTENTS; 1. Overview of ARO program on network science for human decision making B.J. West; 1. Introduction; 2. Background; 2.1. What we know about networks; 2.2. What we do not know about the linking of physical and human networks; 3. What We Have Been Doing; 3.1. Complexity theory and modeling without scales; 3.2. Information propagation in complex adaptive networks; 4. Preliminary Conclusions; References; 2. Viewing the extended mind hypothesis (Clark & Chambers) in terms of complex systems dynamics G. Werner; 1. Background; 2. On the Extended Mind Hypothesis
 3. Brain and World as ONE Complex Dynamical System4. Praxis Ahead of Theory; 5. Conclusion; References; 3. Uncertainty in psychophysics: Deriving a network of psychophysical equations K.H. Norwich; 1. Introduction; 2. Philosophical Underpinnings; 3. Mathematical Representation of the Psychophysical Law (WeberFechner and Stevens); 4. A Network of Equations Issuing from the Entropic Form of the Psychophysical Law; 4.1. The differential threshold (DH from Fechner's conjecture) and Weber's fraction; 4.2. The hyperbolic law governing the magnitude of n (DH from Miller's magical number)
 4.3. Simple reaction time (DH is the minimum quantity of information needed to react)5. Searching for Support within Thermodynamics and Statistical Physics; 5.1. Emergence of the WeberFechner law from thermodynamics; 6. Discussion; 6.1. Review; 6.2. Quantum Sufficiat; Acknowledgements; References; 4. The collective brain E. Tagliazucchi and D.R. Chialvo; 1. Introduction; 2. Emergent Complex Dynamics is always Critical; 3. The Collective Largescale Brain Dynamics; 4. Neuronal Avalanching in Small Scale is Critical; 5. Psychophysics and Behavior; 6. An Evolutionary Perspective
 7. Noise or Critical Fluctuations? Equilibrium vs Nonequilibrium8. Outlook; Acknowledgements; References; 5. Acquiring longrange memory through adaptive avalanches S. Boettcher; 1. Introduction; 2. Motivation from Selforganized Criticality; 3. Spin Glass Ground States with Extremal Optimization; 4. EO Dynamics; 5. Annealed Optimization Model; 6. Evolution Equations for Local Search Heuristics; 6.1. Extremal optimization algorithm; 6.2. Update probabilities for extremal optimization; 6.3. Update probabilities for metropolis algorithms; 6.4. Evolution equations for a simple barrier model
 6.5. Jamming model for EOReferences; 6. Random walk of complex networks: From infinitely slow to instantaneous transition to equilibrium N.W. Hollingshad, P. Grigolini and P. Allegrini; 1. Introduction; 2. Preliminary Remarks on the Size of a Complex Network; 3. On the Master Matrix A; 4. Transition to Equilibrium in Hierarchical Networks; 5. Return to the Origin in a Scalefree Network; 5.1. Ad hoc scalefree network; 5.2. Hierarchical network; 6. Conclusions; Acknowledgements; References; 7. Coherence and complexity M. Bologna, E. Geneston, P. Grigolini, M. Turalska and M. Lukovic
 Control code
 777561001
 Dimensions
 unknown
 Extent
 1 online resource (ix, 196 pages)
 File format
 unknown
 Form of item
 online
 Isbn
 9789814365826
 Level of compression
 unknown
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other physical details
 illustrations
 Quality assurance targets
 not applicable
 Reformatting quality
 unknown
 Sound
 unknown sound
 Specific material designation
 remote
 System control number
 (OCoLC)777561001
Subject
 Psychophysics  Congresses
 Chaotic behavior in systems
 Chaotic behavior in systems  Congresses
 Complexity (Philosophy)
 Complexity (Philosophy)  Congresses
 Conference papers and proceedings
 Congress
 Decision Making
 Decision making  Physiological aspects
 Decision making  Physiological aspects  Congresses
 MEDICAL  Neuroscience
 Neural Networks, Computer
 Neural networks (Neurobiology)
 Neural networks (Neurobiology)  Congresses
 PSYCHOLOGY  Neuropsychology
 Psychophysics
 Psychophysics
Genre
Member of
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