"This book, a reference survey of social simulation work comprehensively collects the most exciting developments in the field. Drawing research contributions from a vibrant community of experts on social simulation, it provides a set of unique and innovative approaches, ranging from agent-based modeling to empirically based simulations, as well as applications in business, governmental, scientific, and other contexts"--Provided by publisher.
This book is the conference proceedings of ESSA 2013, the 9th Conference of the European Social Simulation Association. ESSA conferences constitute annual events, which serve as an international platform for the exchange of ideas and discussion of cutting-edge research in the field of social simulations, both from the theoretical as well as applied perspective. This book consists of 33 articles, which are divided into four themes: Methods for the development of simulation models, Applications of agent-based modeling, Adaptive behavior, social interactions and global environmental change and using qualitative data to inform behavioral rules. We are convinced that this book will serve interested readers as a useful compendium which presents in a nutshell the most recent advances at the frontiers of social simulation research.
This book deals with research in open challenges in Management Engineering in the 21st century, as well as selected opportunities and solutions to remedy them. Management Engineering is an emerging field that extends the analytical methods used in traditional Industrial Engineering and Industrial Organization to address the economic, behavioral and social dimensions of companies and their environments. Management Engineering extends its domain beyond the firm and the market to encompass the modeling and policy design of physical landscapes populated by social agents. The developments of the 21st century have made it necessary to adopt an integrative and global view of the different methodologies and tools that facilitate managers’ decision-making processes, ranging from the strategic to the operational level. This book equips readers with precisely these urgently needed resources.
IDT (Intelligent Decision Technologies) seeks an interchange of research on intelligent systems and intelligent technologies which enhance or improve decision making in industry, government and academia. The focus is interdisciplinary in nature, and includes research on all aspects of intelligent decision technologies, from fundamental development to the applied system. It constitutes a great honor and pleasure for us to publish the works and new research results of scholars from the First KES International Symposium on Intelligent Decision Technologies (KES IDT’09), hosted and organized by University of Hyogo in conjunction with KES International (Himeji, Japan, April, 2009). The symposium was concerned with theory, design, development, implementation, testing and evaluation of intelligent decision systems. Its topics included intelligent agents, fuzzy logic, multi-agent systems, artificial neural networks, genetic algorithms, expert systems, intelligent decision making support systems, information retrieval systems, geographic information systems, and knowledge management systems. These technologies have the potential to support decision making in many areas of management, international business, finance, accounting, marketing, healthcare, military applications, production, networks, traffic management, crisis response, and human interfaces.
Despite being a relatively young sub-discipline, European environmental sociology has changed considerably in the last decades towards more interdisciplinary collaborations and problem solving. Current trends such as global environmental modernization and processes of economic, political and socio-cultural globalization, fuelled by developments of transport, environmental flows, scientific uncertainty, and information technologies, have fostered new conceptual approaches that move beyond classical sociological mind-sets toward broader attempts to connect to other disciplines.
This volume examines all aspects of using agent or individual-based simulation. This approach represents systems as individual elements having their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes this "social" is that it can represent an observed society. Social systems include all those systems where the components have individual agency but also interact with each other. This includes human societies and groups, but also increasingly socio-technical systems where the internet-based devices form the substrate for interaction. These systems are central to our lives, but are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible but, on the other hand, natural language approaches are also inadequate for relating intricate cause and effect. This is why individual and agent-based computational approaches hold out the possibility of new and deeper understanding of such systems. This handbook marks the maturation of this new field. It brings together summaries of the best thinking and practices in this area from leading researchers in the field and constitutes a reference point for standards against which future methodological advances can be judged. This second edition adds new chapters on different modelling purposes and applying software engineering methods to simulation development. Revised existing content will keep the book up-to-date with recent developments. This volume will help those new to the field avoid "reinventing the wheel" each time, and give them a solid and wide grounding in the essential issues. It will also help those already in the field by providing accessible overviews of current thought. The material is divided into four sections: Introduction, Methodology, Mechanisms, and Applications. Each chapter starts with a very brief section called ‘Why read this chapter?’ followed by an abstract, which summarizes the content of the chapter. Each chapter also ends with a section on ‘Further Reading’. Whilst sometimes covering technical aspects, this second edition of Simulating Social Complexity is designed to be accessible to a wide range of researchers, including both those from the social sciences as well as those with a more formal background. It will be of use as a standard reference text in the field and also be suitable for graduate level courses.
Innovation is the creation of new, technologically feasible, commercially realisable products and processes and, if things go right, it emerges from the ongoing interaction of innovative organisations such as universities, research institutes, firms, government agencies and venture capitalists. Innovation in Complex Social Systems uses a "hard science" approach to examine innovation in a new way. Its contributors come from a wide variety of backgrounds, including social and natural sciences, computer science, and mathematics. Using cutting-edge methodology, they deal with the complex aspects of socio-economic innovation processes. Its approach opens up a new paradigm for innovation research, making innovation understandable and tractable using tools such as computational network analysis and agent-based simulation. This book of new work combines empirical analysis with a discussion of the tools and methods used to successfully investigate innovation from a range of international experts, and will be of interest to postgraduate students and scholars in economics, social science, innovation research and complexity science.
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.
This introductory textbook/reference addresses the fundamental and mostly applied kinds of models. The focus is on models of dynamic systems that move and change over time. However, the work also proposes new methods of uncertainty treatment, offering supporting examples. Topics and features: Chapters suitable for textbook use in teaching modeling and simulation Includes sections of questions and answers, helpful in didactic work Proposes new methodology in addition to examining conventional approaches Offers some cognitive, more abstract models to give a wider insight on model building The book’s readership may consist of researchers working on multidisciplinary problems, as well educators and students. It may be used while teaching computer simulation, applied mathematics, system analysis and system dynamics.
This book presents examples of and the latest simulation studies on artificial societies and populations, highlighting innovative implementations of various models of artificial societies and populations using a new, C++-related simulation tool. It demonstrates that the prey-predator models—including spatial distribution, moving patterns, limited renewable food, fear, gregarious (herd) instinct, clustering, epidemics, and competition—are more complex than other publications have suggested, and highlights the great discrepancy between agent-based and conventional continuous models. The book also discusses the modeling and simulation of self-organization and interactions between organizations, including terror organizations, offering fascinating insights into organizational dynamics. The book provides a broad range of examples and comparisons with the classical dynamics approach, showing readers how to construct models of complex systems. It starts with descriptions of the behavior of interacting individuals and also includes important information on the macro-behavior of the whole system.
