Du, Yan, Li, Fangxing, Zandi, Helia, and Xue, Yaosuo. Approximating Nash Equilibrium in Day-ahead Electricity Market Bidding with Multi-agent Deep Reinforcement Learning. Retrieved from https://par.nsf.gov/biblio/10281384. Journal of Modern Power Systems and Clean Energy 9.3 Web. doi:10.35833/MPCE.2020.000502.

Du, Yan, Li, Fangxing, Zandi, Helia, & Xue, Yaosuo. Approximating Nash Equilibrium in Day-ahead Electricity Market Bidding with Multi-agent Deep Reinforcement Learning. Journal of Modern Power Systems and Clean Energy, 9 (3). Retrieved from https://par.nsf.gov/biblio/10281384. https://doi.org/10.35833/MPCE.2020.000502

Du, Yan, Li, Fangxing, Zandi, Helia, and Xue, Yaosuo. "Approximating Nash Equilibrium in Day-ahead Electricity Market Bidding with Multi-agent Deep Reinforcement Learning". Journal of Modern Power Systems and Clean Energy 9 (3). Country unknown/Code not available. https://doi.org/10.35833/MPCE.2020.000502. https://par.nsf.gov/biblio/10281384.

@article{osti_10281384,
place = {Country unknown/Code not available}, title = {Approximating Nash Equilibrium in Day-ahead Electricity Market Bidding with Multi-agent Deep Reinforcement Learning}, url = {https://par.nsf.gov/biblio/10281384}, DOI = {10.35833/MPCE.2020.000502}, abstractNote = {}, journal = {Journal of Modern Power Systems and Clean Energy}, volume = {9}, number = {3}, author = {Du, Yan and Li, Fangxing and Zandi, Helia and Xue, Yaosuo}, editor = {null} }