Network-Oriented Modeling : Addressing Complexity of Cognitive, Affective and Social Interactions

This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation as...

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Main Author: Treur, Jan
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2016, 2016
Edition:1st ed. 2016
Series:Understanding Complex Systems
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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100 1 |a Treur, Jan 
245 0 0 |a Network-Oriented Modeling  |h Elektronische Ressource  |b Addressing Complexity of Cognitive, Affective and Social Interactions  |c by Jan Treur 
250 |a 1st ed. 2016 
260 |a Cham  |b Springer International Publishing  |c 2016, 2016 
300 |a XVI, 499 p. 134 illus., 52 illus. in color  |b online resource 
505 0 |a Preface -- Part I Network-Oriented Modeling: Introduction -- Network-Oriented Modelling and its Conceptual Foundations -- A Temporal-Causal Network Modeling Approach -- Part II Emotions all the Way -- How Emotions Come in between Everything -- How do you Feel Dreaming -- Dreaming your Fear away -- Emotions as a Vehicle for Rationality in Decision Making -- Part III Yourself and the Others -- From Mirroring to the Emergence of Shared Understanding and Collective Power -- Am I going to do this? Is it me who did this -- How Empathical are you -- Are you with me. Am I with you -- Changing yourself, Changing the Other, or Changing your Connection -- Part IV Analysis Methods for Temporal-Causal Network Models -- Where is this going -- What is Happening -- Who are you -- Part V Philosophical, Societal and Educational Perspectives -- We don’t Believe in Ghosts, do we -- Making Smart Applications Smarter -- Multidisciplinary Education -- Part VI Network-Oriented Modelling: Discussion -- On the Use of Network-Oriented Modelling -- Index 
653 |a Data-driven Science, Modeling and Theory Building 
653 |a Computer Appl. in Social and Behavioral Sciences 
653 |a Sociophysics 
653 |a Complexity 
653 |a Applications of Graph Theory and Complex Networks 
653 |a Econophysics 
653 |a Application software 
653 |a Neural networks (Computer science)  
653 |a Computational complexity 
653 |a Physics 
653 |a Mathematical Models of Cognitive Processes and Neural Networks 
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520 |a This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions. Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations of the mental processes of others, and of social phenomena such as shared understandings and collective actions. A variety of sample models – including those for ownership of actions, fear and dreaming, the integration of emotions in joint decision-making based on empathic understanding, and evolving social networks – illustrate the potential of the approach. Dedicated software is available to support building models in a conceptual or graphical manner, transforming them into an executable format and performing simulation experiments. The majority of the material presented has been used and positively evaluated by undergraduate and graduate students and researchers in the cognitive, social and AI domains. Given its detailed coverage, the book is ideally suited as an introduction for graduate and undergraduate students in many different multidisciplinary fields involving cognitive, affective, social, biological, and neuroscience domains