Hazra, Tanmoy. creator author. aut http://id.loc.gov/vocabulary/relators/aut Anjaria, Kushal. author. aut http://id.loc.gov/vocabulary/relators/aut Bajpai, Aditi. author. aut http://id.loc.gov/vocabulary/relators/aut Kumari, Akshara. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text sz 2024 1st ed. 2024. monographic eng

electronic

electronic resource

access XII, 84 p. 8 illus., 4 illus. in color. online resource. 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. 1. Introduction -- 2. Cooperative Game Theory -- 3. Noncooperative Game Theory -- 4. Applications of Game Theory in Deep Neural Networks -- 5. Case Studies and Different Applications -- 6. Conclusion and Future Research Directions. by Tanmoy Hazra, Kushal Anjaria, Aditi Bajpai, Akshara Kumari. Machine learning Game theory Artificial intelligence Machine Learning Game Theory Artificial Intelligence Q325.5-.7 9783031546532 https://doi.org/10.1007/978-3-031-54653-2 https://doi.org/10.1007/978-3-031-54653-2 240319 20251030111729.0 978-3-031-54653-2