An investigation of the relationship between numerical precision and performance of Q-learning for hardware implementation
-
Published:2022
Issue:2
Volume:13
Page:427-433
-
ISSN:2185-4106
-
Container-title:Nonlinear Theory and Its Applications, IEICE
-
language:en
-
Short-container-title:NOLTA
Author:
Oguchi Daisuke1ORCID, Moriya Satoshi2ORCID, Yamamoto Hideaki1ORCID, Sato Shigeo1ORCID
Affiliation:
1. Graduate School of Engineering, Tohoku University 2. Research Institute of Electrical Communication, Tohoku University
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Rehabilitation,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine
Reference10 articles.
1. [1] R. S. Sutton and A. G. Barto, Reinforcement learning, second edition: An introduction. MIT Press, 2018. 2. [2] P. Mirowski, M. Grimes, M. Malinowski, K. M. Hermann, K. Anderson, D. Teplyashin, K. Simonyan, A. Zisserman, R. Hadsell, et al., “Learning to navigate in cities without a map,”Advances in Neural Information Processing Systems, vol. 31, pp. 2419-2430, 2018. 3. [3] A. Kendall, J. Hawke, D. Janz, P. Mazur, D. Reda, J.-M. Allen, V.-D. Lam, A. Bewley, and A. Shah, “Learning to drive in a day,” in 2019 International Conference on Robotics and Automation (ICRA), pp. 8248-8254, IEEE, 2019. 4. [4] P. R. Gankidi and J. Thangavelautham, “FPGA architecture for deep learning and its application to planetary robotics,” in 2017 IEEE Aerospace Conference, pp. 1-9, IEEE, 2017. 5. [5] Z. Wang, C. Li, W. Song, M. Rao, D. Belkin, Y. Li, P. Yan, H. Jiang, P. Lin, M. Hu, et al., “Reinforcement learning with analogue memristor arrays,” Nature Electronics, vol. 2, no. 3, pp. 115-124, 2019.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
|
|