Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation

Reinforcement Learning with Augmented Data

Original

Laskin, M.; Lee, K.; Stooke, A.; Pinto, L.; Abbeel, P.; and Srinivas, A. 2020 · 2004

Earlier work this paper cites.

Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion

Vincent, P.; Larochelle, H.; Lajoie, I.; Bengio, Y.; Manzagol, P.-A.; and Bottou, L. 2010 · 2010

Earlier work this paper cites.

Auto-encoding variational bayes

Original

Kingma, D. P.; and Welling, M. 2013 · 2013

Earlier work this paper cites.

Playing atari with deep reinforcement learning

Original

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

Earlier work this paper cites.

Generative adversarial nets

Goodfellow, I.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A.; and Bengio, Y. 2014 · 2014

Earlier work this paper cites.

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 · 2015

Earlier work this paper cites.

CARLA: An Open Urban Driving Simulator

Dosovitskiy, A.; Ros, G.; Codevilla, F.; Lopez, A.; and Koltun, V. 2017 · 2017

Earlier work this paper cites.

Darla: Improving zero-shot transfer in reinforcement learning

Original

Higgins, I.; Pal, A.; Rusu, A. A.; Matthey, L.; Burgess, C. P.; Pritzel, A.; Botvinick, M.; Blundell, C.; and Lerchner, A. 2017 · 2017

Earlier work this paper cites.

Unsupervised image-to-image translation networks

Liu, M.-Y.; Breuel, T.; and Kautz, J. 2017 · 2017

Cited alongside, same era.

Virtual to real reinforcement learning for autonomous driving

Original

Pan, X.; You, Y.; Wang, Z.; and Lu, C. 2017 · 2017

Cited alongside, same era.

Proximal policy optimization algorithms

Original

Schulman, J.; Wolski, F.; Dhariwal, P.; Radford, A.; and Klimov, O. 2017 · 2017

Cited alongside, same era.

Domain randomization for transferring deep neural networks from simulation to the real world

Tobin, J.; Fong, R.; Ray, A.; Schneider, J.; Zaremba, W.; and Abbeel, P. 2017 · 2017

Cited alongside, same era.

Unpaired image-to-image translation using cycle-consistent adversarial networks

Zhu, J.-Y.; Park, T.; Isola, P.; and Efros, A. A. 2017 · 2017

Cited alongside, same era.

Model-free deep reinforcement learning for urban autonomous driving

Chen, J.; Yuan, B.; and Tomizuka, M. 2019 · 2019

Later among the works it cites.

Learning dexterous in-hand manipulation

Andrychowicz, O. M.; Baker, B.; Chociej, M.; Jozefowicz, R.; McGrew, B.; Pachocki, J.; Petron, A.; Plappert, M.; Powell, G.; Ray, A.; et al. 2020 · 2020

Later among the works it cites.

Curl: Contrastive unsupervised representations for reinforcement learning

Laskin, M.; Srinivas, A.; and Abbeel, P. 2020 · 2020

Later among the works it cites.

Robust Domain Randomization for Reinforcement Learning

Slaoui, R. B.; Clements, W. R.; Foerster, J. N.; and Toth, S. 2020 · 2020

Later among the works it cites.

Adapting deep visuomotor representations with weak pairwise constraints

Tzeng, E.; Devin, C.; Hoffman, J.; Finn, C.; Abbeel, P.; Levine, S.; Saenko, K.; and Darrell, T. 2020 · 2020

Later among the works it cites.

RLCodebase: PyTorch Codebase For Deep Reinforcement Learning Algorithms