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cs.LG2023
Non-Stationary Policy Learning for Multi-Timescale Multi-Agent Reinforcement Learning
Patrick Emami, Xiangyu Zhang, David Biagioni +1
In multi-timescale multi-agent reinforcement learning (MARL), agents interact across different timescales. In general, policies for time-dependent behaviors, such as those induced…
cs.LG2019
Learning Optimal Solutions for Extremely Fast AC Optimal Power Flow
Ahmed Zamzam, Kyri Baker
In this paper, we develop an online method that leverages machine learning to obtain feasible solutions to the AC optimal power flow (OPF) problem with negligible optimality gaps o…