Universal Notice Networks: Transferring Learned Skills Through a Broad Panel of Applications
-
Published:2023-01-23
Issue:2
Volume:107
Page:
-
ISSN:0921-0296
-
Container-title:Journal of Intelligent & Robotic Systems
-
language:en
-
Short-container-title:J Intell Robot Syst
Author:
Mounsif Mehdi, Lengagne SébastienORCID, Thuilot Benoit, Adouane Lounis
Funder
French government research program Investissements d’avenir through the RobotEx Equipment of Excellence IMobS3 Laboratory of Excellence
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Artificial Intelligence,Industrial and Manufacturing Engineering,Mechanical Engineering,Control and Systems Engineering,Software
Reference30 articles.
1. Cunha, J., Serra, R., Lau, N., Lopes, L.S., Neves, A.J.R.: Batch Reinforcement Learning for Robotic Soccer using the Q-batch Update-Rule. Journal of Intelligent & Robotic Systems 80(3), 385–399 (2015) 2. Mnih, V., et al.: Playing atari with deep reinforcement learning. arXiv:1312.5602 (2013) 3. Peng, X.B., Kanazawa, A., Malik, J., Abbeel, P., Levine, S.: SFV: reinforcement learning of physical skills from videos. ACM Trans. Graph 37(6) (2018) 4. Li, Y., Ni, P., Chang, V.: Application of deep reinforcement learning in stock trading strategies and stock forecasting. Journal of Intelligent & Robotic Systems 283–300 (2019) 5. Andrychowicz, O.M., Baker, B., Chociej, M., Józefowicz, R., McGrew, B., Pachocki, J., Petron, A., Plappert, M., Powell, G., Ray, A., Schneider, J., Sidor, S., Tobin, J., Welinder, P., Weng, L., Zaremba, W.: Learning dexterous in-hand manipulation. The International Journal of Robotics Research 39(1), 3–20 (2020)
|
|