Author:
Canese Lorenzo,Cardarilli Gian Carlo,Di Nunzio Luca,Fazzolari Rocco,Re Marco,Spanó Sergio
Publisher
Springer Nature Switzerland
Reference15 articles.
1. Sutton, R., Barto, A.: Reinforcement Learning: An Introduction. A Bradford Book, Cambridge (2018)
2. Rothmann, M., Porrmann, M.: A survey of domain-specific architectures for reinforcement learning. IEEE Access 10, 13753–13767 (2022)
3. Waseem, S.M., Roy, S.K.: Hardware realization of reinforcement learning algorithms for edge devices. In: VLSI and Hardware Implementations Using Modern Machine Learning Methods, pp. 233–254. CRC Press (2021)
4. Su, J.D., Tsai, P.Y.: Processing element architecture design for deep reinforcement learning with flexible block floating point exploiting signal statistics. In: 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), pp. 82–87. IEEE (2020)
5. Watkins, C.J., Dayan, P.: Q-learning. Mach. Learn. 8(3), 279–292 (1992)
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