Back

Topics

enginelearning environmentsmulti-agent reinforcement learningreinforcement learning method

Citation

MLA
Weng, J., et al. “EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine”. Advances in Neural Information Processing Systems 35, 2022, pp. 22409–21, https://doi.org/10.52202/068431-1628.
APA
Weng, J., Lin, M., Huang, S., Liu, B., Makoviichuk, D., Makoviychuk, V., Liu, Z., Song, Y., Luo, T., Jiang, Y., Xu, Z., & Yan, S. (2022). EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine. Advances in Neural Information Processing Systems 35, 22409–22421. https://doi.org/10.52202/068431-1628
Chicago
Weng, J., M. Lin, S. Huang, et al. 2022. “EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine”. Advances in Neural Information Processing Systems 35, 22409–21. https://doi.org/10.52202/068431-1628.
Harvard
Weng, J. et al. (2022) “EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine”, Advances in Neural Information Processing Systems 35. Neural Information Processing Systems Foundation, Inc. (NeurIPS), pp. 22409–22421. Available at: https://doi.org/10.52202/068431-1628.
Vancouver
1. Weng J, Lin M, Huang S, et al (2022) EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine. In: Advances in Neural Information Processing Systems 35. Neural Information Processing Systems Foundation, Inc. (NeurIPS), pp 22409–22421

BibTeX

@inproceedings{Weng_2022, series={NeurIPS 2022}, title={EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine}, url={http://dx.doi.org/10.52202/068431-1628}, DOI={10.52202/068431-1628}, booktitle={Advances in Neural Information Processing Systems 35}, publisher={Neural Information Processing Systems Foundation, Inc. (NeurIPS)}, author={Weng, Jiayi and Lin, Min and Huang, Shengyi and Liu, Bo and Makoviichuk, Denys and Makoviychuk, Viktor and Liu, Zichen and Song, Yufan and Luo, Ting and Jiang, Yukun and Xu, Zhongwen and Yan, Shuicheng}, year={2022}, pages={22409–22421}, collection={NeurIPS 2022} }
Metadata:Crossref

Access the Paper

This paper is available from its original source. Click below to access the PDF.

Open PDF
License: Authors