ns3-gym: Extending OpenAI Gym for Networking Research

G. Carneiro, H. Fontes, and M. Ricardo, “Fast prototyping of network protocols through ns-3 simulation model reuse,” Simulation modelling practice and theory , 2011

2011

Earlier work this paper cites.

K. Winstein and H. Balakrishnan, “Tcp ex machina: Computer-generated congestion control,” in SIGCOMM . ACM, 2013

2013

Earlier work this paper cites.

J. Kober, J. A. Bagnell, and J. Peters, “Reinforcement learning in robotics: A survey,” The International Journal of Robotics Research , vol. 32, no. 11, pp. 1238–1274, 2013

2013

Earlier work this paper cites.

H. Tazaki, F. Uarbani, E. Mancini, M. Lacage, D. Camara, T. Turletti, and W. Dabbous, “Direct code execution: revisiting library OS architecture for reproducible network experiments,” in CoNEXT . ACM, 2013

2013

Earlier work this paper cites.

H. Mao, M. Alizadeh, I. Menache, and S. Kandula, “Resource management with deep reinforcement learning,” in HotNets . ACM, 2016

2016

Earlier work this paper cites.

G. Brockman, V. Cheung, L. Pettersson, J. Schneider, J. Schulman, J. Tang, and W. Zaremba, “OpenAI Gym,” CoRR , 2016. [Online]. Available: http://arxiv.org/abs/1606.01540

Original

2016

Earlier work this paper cites.

C. Buratti and R. Verdone, “L-CSMA: A MAC Protocol for Multihop Linear Wireless (Sensor) Networks,” IEEE Transactions on Vehicular Technology , 2016

2016

Earlier work this paper cites.

I. Zamora, N. G. Lopez, V. M. Vilches, and A. H. Cordero, “Extending the openai gym for robotics: a toolkit for reinforcement learning using ros and gazebo,” arXiv preprint arXiv:1608.05742 , 2016

Original

2016

Cited alongside, same era.

V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu, “Asynchronous Methods for Deep Reinforcement Learning,” CoRR , 2016. [Online]. Available: http://arxiv.org/abs/1602.01783

Original

2016

Cited alongside, same era.

R. Atallah, C. Assi, and M. Khabbaz, “Deep reinforcement learning-based scheduling for roadside communication networks,” in WiOpt , 2017

2017

Cited alongside, same era.

D. S. A. T. Asaf Valadarsky, Michael Schapira, “Learning to route with deep rl,” in NIPS , 2017

2017

Cited alongside, same era.

H. Mao, R. Netravali, and M. Alizadeh, “Neural adaptive video streaming with pensieve,” in SIGCOMM . ACM, 2017

W. Li, F. Zhou, K. R. Chowdhury, and W. M. Meleis, “QTCP: Adaptive Congestion Control with Reinforcement Learning,” IEEE Transactions on Network Science and Engineering , 2018

2018

Closest in time.

Y. Kong, H. Zang, and X. Ma, “Improving TCP Congestion Control with Machine Intelligence,” in NetAI . ACM, 2018

2018

Closest in time.

OpenAI, “OpenAI Gym documentation,” https:gym.openai.com

2018

Closest in time.

——, “OpenAI Gym source code,” https:github.comopenaigym

2018

Closest in time.

NS-3 Consortium, “ns-3 documentation,” https:www.nsnam.org

2018

Closest in time.

——, “ns-3 source code,” http:code.nsnam.org

2018

Closest in time.