Q-Learning for Continuous Actions with Cross-Entropy Guided Policies

Optimization of computer simulation models with rare events

Rubinstein, R. Y · 1997

Earlier work this paper cites.

Reinforcement Learning: An Introduction

Sutton, R. S. and Barto, A. G · 1998

Earlier work this paper cites.

Policy Gradient Methods for Reinforcement Learning with Function Approximation

Sutton, R., McAllester, D., Singh, S. P., and Mansour, Y · 1999

Earlier work this paper cites.

Completely derandomized self-adaptation in evolution strategies

Hansen, N. and Ostermeier, A · 2001

Earlier work this paper cites.

Reinforcement learning in feedback control

Hafner, R. and Riedmiller, M · 2011

Earlier work this paper cites.

Playing Atari with Deep Reinforcement Learning

Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., and Riedmiller, M. A · 2013

Earlier work this paper cites.

Continuous control with deep reinforcement learning: Deep Deterministic Policy Gradients (DDPG)

Lillicrap, T. P., Hunt, J. J., Pritzel, A., Heess, N., Erez, T., Tassa, Y., Silver, D., and Wierstra, D · 2015

Earlier work this paper cites.

OpenAI Gym

Brockman, G., Cheung, V., Pettersson, L., Schneider, J., Schulman, J., Tang, J., and Zaremba, W · 2016

Earlier work this paper cites.

Benchmarking Deep Reinforcement Learning for Continuous Control

Duan, Y., Chen, X., Houthooft, R., Schulman, J., and Abbeel, P · 2016

Earlier work this paper cites.

Asynchronous Methods for Deep Reinforcement Learning arXiv : 1602 . 01783v2 [ cs . LG ] 16 Jun 2016

Mnih, V., Mirza, M., Graves, A., Harley, T., Lillicrap, T. P., and Silver, D · 2016

Cited alongside, same era.

Model-free preference-based reinforcement learning

Wirth, C., Fürnkranz, J., and Neumann, G · 2016

Cited alongside, same era.

Hindsight Experience Replay

Original

Andrychowicz, M., Wolski, F., Ray, A., Schneider, J., Fong, R., Welinder, P., McGrew, B., Tobin, J., Abbeel, P., and Zaremba, W · 2017

Cited alongside, same era.

Reinforcement Learning with Deep Energy-Based Policies

Haarnoja, T., Tang, H., Abbeel, P., and Levine, S · 2017

Cited alongside, same era.

Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control

Original

Islam, R., Henderson, P., Gomrokchi, M., and Precup, D · 2017

Cited alongside, same era.

Composable Deep Reinforcement Learning for Robotic Manipulation

Haarnoja, T., Pong, V., Zhou, A., Dalal, M., Abbeel, P., and Levine, S · 2018

Later among the works it cites.

Deep Reinforcement Learning That Matters

Henderson, P., Islam, R., Bachman, P., Pineau, J., Precup, D., and Meger, D · 2018

Later among the works it cites.

Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation

Kalashnikov, D., Irpan, A., Pastor, P., Ibarz, J., Herzog, A., Jang, E., Quillen, D., Holly, E., Kalakrishnan, M., Vanhoucke, V., and Levine, S · 2018

Later among the works it cites.

Evolution-guided policy gradient in reinforcement learning

Original

Khadka, S. and Tumer, K · 2018

Later among the works it cites.

Sim-to-Real Reinforcement Learning for Deformable Object Manipulation

Matas, J., James, S., and Davison, A. J · 2018

Later among the works it cites.