Continuous control with deep reinforcement learning
Original
Lillicrap, T. P., Hunt, J. J., Pritzel, A., Heess, N., Erez, T., Tassa, Y., Silver, D., and Wierstra, D · 2015
Cited alongside, same era.
Human-level control through deep reinforcement learning
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., et al · 2015
Cited alongside, same era.
Trust region policy optimization
Schulman, J., Levine, S., Abbeel, P., Jordan, M., and Moritz, P · 2015
Cited alongside, same era.
A gaussian mixture model layer jointly optimized with discriminative features within a deep neural network architecture
Variani, E., McDermott, E., and Heigold, G · 2015
Cited alongside, same era.
Dueling network architectures for deep reinforcement learning
Original
Wang, Z., Schaul, T., Hessel, M., Van Hasselt, H., Lanctot, M., and De Freitas, N · 2015
Cited alongside, same era.
Embed to control: A locally linear latent dynamics model for control from raw images
Watter, M., Springenberg, J., Boedecker, J., and Riedmiller, M · 2015
Cited alongside, same era.
Making contextual decisions with low technical debt
Original
Agarwal, A., Bird, S., Cozowicz, M., Hoang, L., Langford, J., Lee, S., Li, J., Melamed, D., Oshri, G., Ribas, O., et al · 2016
Cited alongside, same era.
Openai gym
Original
Brockman, G., Cheung, V., Pettersson, L., Schneider, J., Schulman, J., Tang, J., and Zaremba, W · 2016
Cited alongside, same era.
Doubly robust off-policy value evaluation for reinforcement learning
Jiang, N. and Li, L · 2016
Cited alongside, same era.
Data-efficient off-policy policy evaluation for reinforcement learning
Thomas, P. and Brunskill, E · 2016
Cited alongside, same era.
Deep reinforcement learning with double q-learning
Van Hasselt, H., Guez, A., and Silver, D · 2016
Cited alongside, same era.
A distributional perspective on reinforcement learning
Original
Bellemare, M. G., Dabney, W., and Munos, R · 2017
Cited alongside, same era.