TY  - GEN
AB  - 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.
AU  - Lee, Juhyoung,
AU  - Yoo, Hoi-Jun,
CN  - Q325.73
DO  - 10.1007/978-3-031-36793-9
DO  - doi
ID  - 1476191
KW  - Deep learning (Machine learning)
KW  - Reinforcement learning.
KW  - Mobile communication systems
KW  - Apprentissage profond.
KW  - Apprentissage par renforcement (Intelligence artificielle)
KW  - Radiocommunications mobiles
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-36793-9
N2  - 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.
SN  - 9783031367939
SN  - 3031367936
T1  - Deep reinforcement learning processor design for mobile applications /
TI  - Deep reinforcement learning processor design for mobile applications /
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-36793-9
ER  -