Modelling Stochastic Uncertainties: From Monte Carlo Simulations to Game Theory

Modelling Stochastic Uncertainties: From Monte Carlo Simulations to Game Theory (De Gruyter Textbook)

Author: Mohammed Elmusrati (Author)

Publisher finelybook 出版社:‏ De Gruyter

Edition 版本:‏ 1st edition

Publication Date 出版日期:‏ 2024-11-18

Language 语言: English

Perfect Print Length 页数: 332 pages

ISBN-10: 3111584704

ISBN-13: 9783111584706

Book Description

This book delves into dynamic systems modeling, probability theory, stochastic processes, estimation theory, Kalman filters, and game theory. While many excellent books offer insights into these topics, our proposed book takes a distinctive approach, integrating these diverse subjects to address uncertainties and demonstrate their practical applications.

The author aims to cater to a broad spectrum of readers. The book features approximately 150 meticulously explained solved examples and numerous simulation programs, each with detailed explanations.

“Modelling Stochastic Uncertainties” provides a comprehensive understanding of uncertainties and their implications across various domains. Here is a brief exploration of the chapters:

Chapter 1: Introduces the book’s philosophy and the manifestation of uncertainties.

Chapter 2: Lays the mathematical foundation, focusing on probability theory and stochastic processes, covering random variables, probability distributions, expectations, characteristic functions, and limits, along with various stochastic processes and their properties.

Chapter 3: Discusses managing uncertainty through deterministic and stochastic dynamic modeling techniques.

Chapter 4: Explores parameter estimation amid uncertainty, presenting key concepts of estimation theory.

Chapter 5: Focuses on Kalman filters for state estimation amid uncertain measurements and Gaussian additive noise.

Chapter 6: Examines how uncertainty influences decision-making in strategic interactions and conflict management.

Overall, the book provides a thorough understanding of uncertainties, from theoretical foundations to practical applications in dynamic systems modeling, estimation, and game theory.

About the Author

Dr. Mohammed S. Elmusrati, Senior Member of IEEE, began his academic journey at the University of Benghazi, Libya, where he earned his B.Sc. degree with Honors in 1991 and his M.Sc. degree with High Honors in 1995. He continued his pursuit of excellence at Aalto University in Finland, obtaining a Licentiate of Science in Technology with Distinction in 2002 and a Doctor of Science in Technology (D.Sc.) in Automation and Control Engineering in 2004. Currently, Dr. Elmusrati is a Full Professor of Communication, Automation, and Smart Systems at the School of Technology and Innovations, University of Vaasa, Finland.

Dr. Elmusrati has made significant contributions to international academic programs, including the development of Communication and Systems Engineering, Wireless Automation, and Industrial Digitalization programs. He also heads the international program for Sustainable and Autonomous Systems (SAS). His research interests are diverse, covering wireless communications, artificial intelligence, machine learning, biotechnology, data analysis, stochastic systems, smart grids, and game theory.

With an extensive publication record, Dr. Elmusrati has authored over 180 papers, books, and book chapters. He has supervised more than 120 master’s theses and 12 Ph.D. students. His innovative contributions were recognized when he was awarded the Inventor of the Year 2024 at the University of Vaasa.

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