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Applications of game theory in deep learning / by Tanmoy Hazra, Kushal Anjaria, Aditi Bajpai, Akshara Kumari

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: SpringerBriefs in Computer SciencePublisher: Cham : Springer Nature Switzerland, 2024Publisher: Cham : Imprint: Springer, 2024Edition: 1st ed. 2024Description: 1 Online-Ressource(XII, 84 p. 8 illus., 4 illus. in color.)ISBN:
  • 9783031546532
Subject(s): Additional physical formats: 9783031546525 | 9783031546549 | Erscheint auch als: 9783031546525 Druck-Ausgabe | Erscheint auch als: 9783031546549 Druck-Ausgabe | Erscheint auch als: Applications of game theory in deep learning. Druck-Ausgabe Cham : Springer, 2024. xii, 84 SeitenDOI: DOI: 10.1007/978-3-031-54653-2Online resources: Summary: 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.Summary: 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.PPN: PPN: 1884356648Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SCS | ZDB-2-SXCS
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