Deep Reinforcement Learning Processor Design for Mobile Applications
This book discusses the acceleration of deep reinforcement learning (DRL), which may be the next step in the burst success of artificial intelligence (AI). The authors address acceleration systems which enable DRL on area-limited & battery-limited mobile devices. Methods are described that enabl...
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| Hlavní autoři: | , |
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| Korporativní autor: | |
| Médium: | Elektronický zdroj E-kniha |
| Jazyk: | angličtina |
| Vydáno: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2023.
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| Vydání: | 1st ed. 2023. |
| Témata: | |
| On-line přístup: | https://doi.org/10.1007/978-3-031-36793-9 |
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| Shrnutí: | This book discusses the acceleration of deep reinforcement learning (DRL), which may be the next step in the burst success of artificial intelligence (AI). The authors address acceleration systems which enable DRL on area-limited & battery-limited mobile devices. Methods are described that enable DRL optimization at the algorithm-, architecture-, and circuit-levels of abstraction. Enables deep reinforcement learning (DRL) optimization at algorithm-, architecture-, and circuit-levels of abstraction; Includes methodologies that can reduce the high cost of DRL; Uses analysis of computational workload characteristics of DRL in the context of acceleration. |
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| Fyzický popis: | 1 online resource (VI, 101 p. 63 illus.). 55 illus. in color. |
| ISBN: | 9783031367939 |
| DOI: | 10.1007/978-3-031-36793-9 |