An Introduction to Agent-Based Modeling
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.
About the Authors
Uri Wilensky is Professor of Learning Sciences, Computer Science, and Complex Systems at Northwestern University and Director of the Center for Connected Learning and Computer-Based Modeling there. He is the author of the NetLogo language.
William Rand is Assistant Professor of Marketing and Computer Science and Director of the Center for Complexity in Business at the Robert H. Smith School of Business at the University of Maryland.
—Robert Goldstone, Chancellor's Professor of Psychological and Brain Sciences, Indiana University Bloomington
—Melanie Mitchell, Professor, Portland State University and the Santa Fe Institute; author of Complexity: A Guided Tour
—Joshua M. Epstein, Johns Hopkins University and the Santa Fe Institute