Strategic Applications Of Game Theory
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Strategic Applications of Game Theory
Author: Parthiban Srinivasan
language: en
Publisher: Educohack Press
Release Date: 2025-02-20
"Strategic Applications of Game Theory" is an indispensable resource that delves into the intricacies of game theory, offering a thorough exploration of fundamental concepts, practical applications, and recent developments. Whether you're a student, researcher, or practitioner, this book serves as your definitive guide to understanding the principles and real-world implications of game theory across various disciplines. We begin by laying a solid foundation in game theory basics, including definitions, origins, and the evolution of key concepts. Readers are introduced to strategic interactions, decision-making processes, and the mathematical frameworks underpinning game-theoretic analyses. As the journey progresses, we delve into advanced topics such as cooperative and non-cooperative games, equilibrium concepts, and mechanism design, providing a deep understanding of strategic reasoning and solution concepts. Covering a wide range of topics, from classical game theory to cutting-edge research in behavioral game theory and machine learning, we present complex theories in a clear and accessible manner. Real-world examples illustrate game theory applications in economics, political science, biology, computer science, and other fields. Engaging exercises encourage readers to apply their understanding and develop analytical skills. Drawing on insights from economics, mathematics, psychology, and computer science, this interdisciplinary approach offers a holistic perspective on strategic behavior.
Game Theory with Applications to Economics
Author: James W. Friedman
language: en
Publisher: Oxford University Press, USA
Release Date: 1990
Drawing on examples from current economic literature and politics, this is the first book on game theory at an introductory, but not elementary, level. The author covers topics of great actual or potential use in economics, such as noncooperative games, infinitely repeated games, finitely repeated games, two-person cooperative games, and cooperative games with and without side payments. Thoroughly revised, the new second edition of this authoritative book includes greatly expanded coverage of equilibrium refinements, and the "folk theorem" for repeated games as well as a new chapter on finite noncooperative games.
Applications of Game Theory in Deep Learning
This book aims to unravel the complex tapestry that interweaves strategic decision-making models with the forefront of deep learning techniques. Applications of Game Theory in Deep Learning provides an extensive and insightful exploration of game theory in deep learning, diving deep into both the theoretical foundations and the real-world applications that showcase this intriguing intersection of fields. Starting with the essential foundations for comprehending both game theory and deep learning, delving into the individual significance of each field, the book culminates in a nuanced examination of Game Theory's pivotal role in augmenting and shaping the development of Deep Learning algorithms. By elucidating the theoretical underpinnings and practical applications of this synergistic relationship, we equip the reader with a comprehensive understanding of their combined potential. In our digital age, where algorithms and autonomous agents are becoming more common, the combination of game theory and deep learning has opened a new frontier of exploration. The combination of these two disciplines opens new and exciting avenues. We observe how artificial agents can think strategically, adapt to ever-shifting environments, and make decisions that are consistent with their goals and the dynamics of their surroundings. This book presents case studies, methodologies, and real-world applications.