# Introduction to the Modeling and Analysis of Complex Systems

(1 review)

Hiroki Sayama, State University of New York at Binghamton

Pub Date: 2015

ISBN 13: 9781942341093

Publisher: Open SUNY

Language: English

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## Conditions of Use

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CC BY-NC-SA

## Reviews

This is more like an encyclopedia of modeling complex systems. Please take it as a compliment. This is an excellent book on the topic which can be used by engineers, computer scientists, physicists, bio-scientists, and almost everyone who needs... read more

## Table of Contents

- Chapter 1 Introduction
- Chapter2 Fundamentals of Modeling
- Chapter3 Basics of Dynamical Systems
- Chapter4 Discrete-Time Models I: Modeling
- Chapter5 Discrete-Time Models II: Analysis
- Chapter6 Continuous-Time Models I: Modeling
- Chapter7 Continuous-Time Models II: Analysis
- Chapter8 Bifurcations
- Chapter9 Chaos
- Chapter10 Interactive Simulation of Complex Systems
- Chapter11 Cellular Automata I: Modeling
- Chapter12 Cellular Automata II: Analysis
- Chapter13 Continuous Field Models I: Modeling
- Chapter14 Continuous Field Models II: Analysis
- Chapter15 Basics of Networks
- Chapter16 Dynamical Networks I: Modeling
- Chapter17 Dynamical Networks II: Analysis of Network Topologies
- Chapter18 Dynamical Networks III: Analysis of Network Dynamics
- Chapter19 Agent-Based Models

## About the Book

*Introduction to the Modeling and Analysis of Complex Systems* introduces students to mathematical/computational modeling and analysis developed in the emerging interdisciplinary field of Complex Systems Science. Complex systems are systems made of a large number of microscopic components interacting with each other in nontrivial ways. Many real-world systems can be understood as complex systems, where critically important information resides in the relationships between the parts and not necessarily within the parts themselves.

This textbook offers an accessible yet technically-oriented introduction to the modeling and analysis of complex systems. The topics covered include: fundamentals of modeling, basics of dynamical systems, discrete-time models, continuous-time models, bifurcations, chaos, cellular automata, continuous field models, static networks, dynamic networks, and agent-based models. Most of these topics are discussed in two chapters, one focusing on computational modeling and the other on mathematical analysis. This unique approach provides a comprehensive view of related concepts and techniques, and allows readers and instructors to flexibly choose relevant materials based on their objectives and needs. Python sample codes are provided for each modeling example.

## About the Contributors

### Author

**Hiroki Sayama**, D.Sc., is an Associate Professor in the Department of Systems Science and Industrial Engineering, and the Director of the Center for Collective Dynamics of Complex Systems (CoCo), at Binghamton University, State University of New York. He received his BSc, MSc and DSc in Information Science, all from the University of Tokyo, Japan. He did his postdoctoral work at the New England Complex Systems Institute in Cambridge, Massachusetts, from 1999 to 2002. His research interests include complex dynamical networks, human and social dynamics, collective behaviors, artificial life/chemistry, and interactive systems, among others. He is an expert of mathematical/computational modeling and analysis of various complex systems. He has published more than 100 peer-reviewed journal articles and conference proceedings papers and has edited eight books and conference proceedings about complex systems related topics. His publications have acquired more than 2000 citations as of July 2015. He currently serves as an elected Board Member of the International Society for Artificial Life (ISAL) and as an editorial board member for Complex Adaptive Systems Modeling (SpringerOpen), International Journal of Parallel, Emergent and Distributed Systems (Taylor & Francis), and Applied Network Science (SpringerOpen).