Agent Based Simulation Of Vulnerability Dynamics
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Agent-Based Simulation of Vulnerability Dynamics
Author: Cilli Sobiech
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-10-11
This thesis constitutes an extraordinary innovative research approach in transferring the concepts and methods of complex systems to risk research. It ambitiously bridges the barriers between theoretical, empirical and methodical research work and integrates these fields into one comprehensive approach of dealing with uncertainty in socio-ecological systems. The developed agent-based simulation aims at the dynamics of social vulnerability in the considered system of the German North Sea Coast. Thus, the social simulation provides an analytical method to explore the individual, relational, and spatial aspects leading to dynamics of vulnerability in society. Combining complexity science and risk research by the method of agent-based simulation hereby emphasizes the importance of understanding interrelations inside the system for the system's development, i.e. for the evolving. Based on a vulnerability assessment regarding vulnerability characteristics, present risk behavior and self-protection preferences of private households against the impacts of flooding and storm surges, possible system trajectories could be explored by means of simulation experiments. The system-analytical approach therefore contributes to an integrated consideration of multi-dimensional and context-sensitv social phenomena such as vulnerability. Furthermore it achieves conceptually and strategically relevant implications for risk research and complex systems research.
Agent-Based Simulation of Vulnerability Dynamics
Author: Cilli Sobiech
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-10-10
This thesis constitutes an extraordinary innovative research approach in transferring the concepts and methods of complex systems to risk research. It ambitiously bridges the barriers between theoretical, empirical and methodical research work and integrates these fields into one comprehensive approach of dealing with uncertainty in socio-ecological systems. The developed agent-based simulation aims at the dynamics of social vulnerability in the considered system of the German North Sea Coast. Thus, the social simulation provides an analytical method to explore the individual, relational, and spatial aspects leading to dynamics of vulnerability in society. Combining complexity science and risk research by the method of agent-based simulation hereby emphasizes the importance of understanding interrelations inside the system for the system's development, i.e. for the evolving. Based on a vulnerability assessment regarding vulnerability characteristics, present risk behavior and self-protection preferences of private households against the impacts of flooding and storm surges, possible system trajectories could be explored by means of simulation experiments. The system-analytical approach therefore contributes to an integrated consideration of multi-dimensional and context-sensitv social phenomena such as vulnerability. Furthermore it achieves conceptually and strategically relevant implications for risk research and complex systems research.
Agent-Based Modeling and Network Dynamics
Author: Akira Namatame
language: en
Publisher: Oxford University Press
Release Date: 2016-01-28
While the significance of networks in various human behavior and activities has a history as long as human's existence, network awareness is a recent scientific phenomenon. The neologism network science is just one or two decades old. Nevertheless, with this limited time, network thinking has substantially reshaped the recent development in economics, and almost all solutions to real-world problems involve the network element. This book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The authors begin with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling's segregation model and Axelrod's spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The text also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. It reviews a number of pioneering and representative models in this family. Upon the given foundation, the second part reviews three primary forms of network dynamics, such as diffusions, cascades, and influences. These primary dynamics are further extended and enriched by practical networks in goods-and-service markets, labor markets, and international trade. At the end, the book considers two challenging issues using agent-based models of networks: network risks and economic growth.