114 Result(s)
within
Chapter
Jan Treur
Information Systems Applications (incl. Internet)
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Chapter and Conference Paper
‘If Only I Would Have Done that…’: A Controlled Adaptive Network Model for Learning by Counterfactual Thinking
In this paper counterfactual thinking is addressed based on literature mainly from Neuroscience and Psychology. A detailed literature review was conducted in identifying processes, neural correlates and theori...
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Chapter and Conference Paper
A Computational Network Model for Shared Mental Models in Hospital Operation Rooms
This paper describes a network model for mental processes making use of shared mental models (SMM) of team performance. The paper illustrates the value of adequate SMM’s for safe and efficient team performance...
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Chapter and Conference Paper
A Computational Model for the Second-Order Adaptive Causal Relationships Between Anxiety, Stress and Physical Exercise
Mental disorders are more and more seen as based on complex networks of symptoms and predispositions that create the disorder as an emergent behaviour of the network’s dynamics. This paper aims to provide a co...
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Chapter
Using Network Reification for Adaptive Networks: Discussion
In this final chapter, the most important or most remarkable themes recurring at different places in this book are briefly summarized and reviewed. Subsequently the following themes are addressed: (1) How netw...
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Chapter
A Modeling Environment for Reified Temporal-Causal Network Models
The introduced multilevel reified (temporal-causal) network architecture is the basis of the implementation of a dedicated software environment developed by the author in Matlab. The environment includes a com...
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Chapter
On the Universal Combination Function and the Universal Difference Equation for Reified Temporal-Causal Network Models
The universal differential and difference equation form an important basis for reified temporal-causal networks and their implementation. In this chapter, a more in depth analysis is presented of the universal...
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Chapter
On Adaptive Networks and Network Reification
This chapter is a brief preview of what can be expected in this book, with some pointers to various chapters and sections. First, it is discussed how networks can be adaptive in different ways and according to...
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Chapter
Analysis of a Network’s Emerging Behaviour via Its Structure Involving Its Strongly Connected Components
In this chapter, it is addressed how network structure can be related to network behaviour. If such a relation is studied, that usually concerns only strongly connected networks and only linear functions descr...
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Chapter
A Unified Approach to Represent Network Adaptation Principles by Network Reification
In this chapter, the notion of network reification is introduced: a construction by which a given (base) network is extended by adding explicit states representing the characteristics defining the base network...
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Chapter
Relating a Reified Adaptive Network’s Emerging Behaviour Based on Hebbian Learning to Its Reified Network Structure
In this chapter another challenge is analysed for how emerging behaviour of an adaptive network can be related to characteristics of the adaptive network’s structure. By applying network reification, the adapt...
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Chapter
A Reified Network Model for Adaptive Decision Making Based on the Disconnect-Reconnect Adaptation Principle
In recent literature from Neuroscience, the adaptive role of the effects of stress on decision making is highlighted. In this chapter, it is addressed how that role can be modelled computationally using a reif...
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Chapter
Modeling Higher-Order Adaptive Evolutionary Processes by Reified Adaptive Network Models
In this chapter, a fourth-order reified network model is introduced to describe different orders of adaptivity found in a case study on evolutionary processes. The network model describes how the causal pathwa...
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Chapter
Relating Emerging Network Behaviour to Network Structure
Emerging behaviour of a network is a consequence of the network’s structure. However, it may often not be easy to find out how this relation between structure and behaviour exactly is. In this chapter, results...
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Chapter
Ins and Outs of Network-Oriented Modeling
Network-Oriented Modeling has successfully been applied to obtain network models for a wide range of phenomena, including Biological Networks, Mental Networks, and Social Networks. In this chapter, it is discu...
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Chapter
Relating a Reified Adaptive Network’s Structure to Its Emerging Behaviour for Bonding by Homophily
In this chapter it is analysed how emerging behaviour in an adaptive social network for bonding can be related to characteristics of the adaptive network’s structure, which includes the structure of the adapta...
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Chapter
Modeling Higher-Order Network Adaptation by Multilevel Network Reification
In network models for real-world domains, often some form of network adaptation has to be incorporated, based on certain network adaptation principles. In some cases, also higher-order adaptation occurs: the a...
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Chapter
Mathematical Details of Specific Difference and Differential Equations and Mathematical Analysis of Emerging Network Behaviour
In this chapter, additional mathematical details are presented for many of the chapters concerning the specific difference and differential equations, and mathematical analysis of emerging behaviour. For model...
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Chapter
Using Multilevel Network Reification to Model Second-Order Adaptive Bonding by Homophily
The concept of multilevel network reification introduced in the previous chapters enables representation within a network not only of first-order adaptation principles, but also of second-order adaptation prin...
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Chapter
Higher-Order Reified Adaptive Network Models with a Strange Loop
In this chapter, as in Chap. 7, the challenge of exploring plausible reified network models of order higher than two is addressed. This time another less usu...
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Chapter and Conference Paper
A Second-Order Adaptive Social-Cognitive Agent Model for Prisoner Recidivism
In this study, a second-order adaptive social-cognitive agent model is introduced to examine prisoner recidivism. For comparison between different kinds of prisons and prison policies, recidivism rates from No...
