Téléchargez le livre : Deep Reinforcement Learning for Wireless Networks
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Description

This Springerbrief presents a deep reinforcement learning approach to wireless systems to improve system performance. Particularly, deep reinforcement learning approach is used in cache-enabled opportunistic interference alignment wireless networks and mobile social networks. Simulation results with different network parameters are presented to show the effectiveness of the proposed scheme.
 There is a phenomenal burst of research activities in artificial intelligence, deep reinforcement learning and wireless systems. Deep reinforcement learning has been successfully used to solve many practical problems. For example, Google DeepMind adopts this method on several artificial intelligent projects with big data (e.g., AlphaGo), and gets quite good results..
 Graduate students in electrical and computer engineering, as well as computer science will find this brief useful as a study guide. Researchers, engineers, computer scientists, programmers, and policy makers will also find this brief to be a useful tool. 
Pages
71 pages
Collection
SpringerBriefs in Electrical and Computer Engineering
Parution
2019-01-17
Marque
Springer
EAN papier
9783030105457
EAN PDF
9783030105464
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
7
Taille du fichier
2540 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
63,29 €
EAN EPUB
9783030105464
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
7
Taille du fichier
8018 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
63,29 €

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