Auteur
Dr. Erik Cuevas received his Ph.D. degree from Freie Universität Berlin, Germany in 2006. Since 2006 he has been with the University of Guadalajara, where he is currently a full-time Professor in the Department of Computer Science. Since 2008, he has been a member of the Mexican National Research System (SNI III). He is the author of several books, including Metaheuristic Computation with MATLAB, Taylor and Francis/CRC Press; Recent Metaheuristic Computation Schemes in Engineering, Springer; Recent Metaheuristic Algorithms for Parameter Identification, Springer; and Metaheuristic Computation: A Performance Perspective, Springer, among others. His current research interests include meta-heuristics, computer vision, and mathematical methods. He serves as an Editor for the journals Expert System with Applications, ISA Transactions, Applied Soft Computing, Applied Mathematical Modeling, and Mathematics and Computers in Simulation. Karla Avila received her M.Sc. degree in Electronics and Computer Engineering from University of Guadalajara in 2020. She is currently enrolled in the Ph.D. program in Electronics and Computer Science at University of Guadalajara, and her current research interests include artificial intelligence, modeling complex systems, and metaheuristic algorithms.Miguel Islas Toski received his M.Sc. in Electronics and Computer Engineering from University of Guadalajara in 2020. He completed an internship at Arizona State University in 2017. He is currently enrolled in the Ph.D. program in Electronics and Computer Science at University of Guadalajara, and his current research interests include artificial intelligence, evolutionary algorithms, agent-based modeling, and smart and sustainable cities.Héctor Escobar received his M.Sc. degree in Electronics and Computer Engineering from the University of Guadalajara, Mexico, in 2021. He is currently enrolled in the Ph.D. program in Electronics and Computer Science at University of Guadalajara, and his current research interests include meta-heuristics, computer vision, artificial intelligence, and Agent-Based Modeling.

Texte du rabat
As the world becomes more complicated and linked, many of our research questions can no longer be answered using straightforward models. Agent-Based Models with MATLAB introduces one of the most important methodologies for complex systems modeling, called Agent-Based Modeling (ABM), using computational implementations and accompanying MATLAB software code as a means of inspiring readers to apply agent-based models to solve a diverse range of problems. Observing the implementation of a particular approach through code can be helpful for readers, even those with strong mathematical abilities, as it eliminates ambiguities and uncertainties, making the material easier to grasp and communicate. The book comes with a large amount of software code accompanying the main text, and the modeling systems described in the book are implemented using MATLAB as the programming language. Despite the heavy mathematical components of Agent-Based Models and complex systems, it is possible to utilize these models without in-depth understanding of their mathematical fundamentals. For many readers, a more feasible goal is to grasp the concepts of these models through programming instead of mathematical formulations. Agent-Based Models with MATLAB enables computer scientists, mathematicians, researchers and engineers to apply ABM in a wide range of research and engineering applications. The book gradually advances from basic to more advanced methods, while reinforcing understanding of complex systems through practical, hands-on applications of various computational models.

Contenu

Introduction 2. Agents 3. Agent-based modeling 4. Complex networks and graph theory 5. Cellular Automata 6. Validation Framework 7. Model applications 8. Differences between Cellular Automata and Agent-Based Models 9. Implementations of agent-based models