Description: Learning-Driven Game Theory for AI: Concepts, Models, and Applications offers in-depth coverage of recent methodological and conceptual advancements in various disciplines of Dynamic Games, namely differential and discrete-time dynamic games, evolutionary games, repeated and stochastic games, and their applications in a variety of fields, such as computer science, biology, economics, and management science. In this book, the authors bridge the gap between traditional game theory and its modern applications in artificial intelligence (AI) and related technological fields. The dynamic nature of contemporary problems in robotics, cybersecurity, machine learning, and multi-agent systems requires game-theoretic solutions that go beyond classical methods. The book delves into the rapidly growing intersection of pursuit differential games and AI, focusing on how these advanced game-theoretic models can be applied to modern AI systems, making it an indispensable resource for both academics and professionals. The book also provides a variety of applications demonstrating the practical integration of AI and game theory across various disciplines, such as autonomous systems, federated learning, and distributed decision-making frameworks. The book also explores the use of game theory in reinforcement learning, swarm intelligence, multi-agent coordination, and cybersecurity. These are critical areas where AI and dynamic games converge. Each chapter covers a different facet of dynamic games, offering readers a comprehensive yet focused exploration of topics such as differential and discrete-time games, evolutionary dynamics, and repeated and stochastic games. The absence of static games ensures a concentrated focus on the dynamic, evolving problems that are most relevant today.
Brief description: Dr. Mehdi Salimi is an accomplished faculty member with a diverse academic background, having held positions at several Canadian universities, including KPU, StFX, and McMaster University. He earned his Ph.D. in applied mathematics from UPM in 2011 and previously obtained a master's degree in pure mathematics from Tehran, Iran, in 2006. Dr. Salimi has served as a visiting professor at UniRC and a research fellow at the MEDAlics Research Centre at the University "Dante Alighieri" in Italy. He completed a postdoctoral fellowship at the Center for Dynamics (CfD) at Dresden University of Technology, Germany, in January 2015 and is now a senior member of the faculty there. Additionally, he is part of the Decisions Lab at DiGiES, University of Reggio Calabria, Italy. Dr. Salimi has published around 80 articles, showcasing his expertise in Game Theory, Dynamical Systems, and Data Science. His contributions extend to editorial roles in several prestigious journals, reflecting his commitment to advancing scientific knowledge and fostering academic dialogue in his fields of interest. Moreover, Dr. Salimi has made valuable contributions as an editorial member of esteemed journals, including Mathematical Methods of Operations Research, Journal of Optimization Theory and Applications, Annals of Operations Research, Soft Computing, Dynamic Games and Applications, Results in Control and Optimization, Engineering Science and Technology an International Journal, Mathematics, and Sustainable Computing: Informatics and Systems.