Agent Based Simulation Of Organizational Behavior
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Agent-Based Simulation of Organizational Behavior
The aim of this book is to demonstrate how Agent-Based Modelling (ABM) can be used to enhance the study of social agency, organizational behavior and organizational management. It derives from a workshop, sponsored by the Society for the Study of Artificial Intelligence and the Simulation of Behavior (AISB), held at Bournemouth University Business School in 2014 on “Modelling Organizational Behavior and Social Agency”. The contents of this book are divided into four themes: Perspectives, Modeling Organizational Behavior, Philosophical and Methodological Perspective, and Modeling Organized Crime and Macro-Organizational Phenomena. ABM is a particular and advanced type of computer simulation where the focus of modeling shifts to the agent rather than to the system. This allows for complex and more realistic representations of reality, facilitating an innovative socio-cognitive perspective on organizational studies. The editors and contributing authors claim that the use of ABM may dramatically expand our understanding of human behavior in organizations. This is made possible because of (a) the computational power made available by technological advancements, (b) the relative ease of the programming, (c) the ability to borrow simulation practices from other disciplines, and (d) the ability to demonstrate how the ABM approach clearly enables a socio-cognitive perspective on organizational complexity. Showcasing contributions from academics and researchers of various backgrounds and discipline, this volumes provides a global, interdisciplinary perspective.
Agent-Based Computational Modelling
Author: Francesco C. Billari
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-06-14
The present book describes the methodology to set up agent-based models and to study emerging patterns in complex adaptive systems resulting from multi-agent interaction. It offers the application of agent-based models in demography, social and economic sciences and environmental sciences. Examples include population dynamics, evolution of social norms, communication structures, patterns in eco-systems and socio-biology, natural resource management, spread of diseases and development processes. It presents and combines different approaches how to implement agent-based computational models and tools in an integrative manner that can be extended to other cases.
An Introduction to Agent-Based Modeling
A comprehensive and hands-on introduction to the core concepts, methods, and applications of agent-based modeling, including detailed NetLogo examples. The advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, across domains that range from engineering to ecology. An Introduction to Agent-Based Modeling offers a comprehensive description of the core concepts, methods, and applications of ABM. Its hands-on approach—with hundreds of examples and exercises using NetLogo—enables readers to begin constructing models immediately, regardless of experience or discipline. The book first describes the nature and rationale of agent-based modeling, then presents the methodology for designing and building ABMs, and finally discusses how to utilize ABMs to answer complex questions. Features in each chapter include step-by-step guides to developing models in the main text; text boxes with additional information and concepts; end-of-chapter explorations; and references and lists of relevant reading. There is also an accompanying website with all the models and code.