Twin-Delayed Deep Deterministic Policy Gradient Algorithm to Control a Boost Converter in a DC Microgrid
PulseAugur coverage of Twin-Delayed Deep Deterministic Policy Gradient Algorithm to Control a Boost Converter in a DC Microgrid — every cluster mentioning Twin-Delayed Deep Deterministic Policy Gradient Algorithm to Control a Boost Converter in a DC Microgrid across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
-
New framework uses graph neural networks for dynamic railway pricing
A new research paper introduces a novel framework for dynamic pricing in liberalized high-speed railway markets. The approach uses relational multi-agent reinforcement learning with a graph convolutional network to mode…
-
Reinforcement learning uses dynamic entropy tuning for better quadcopter control
Researchers have investigated the impact of dynamic entropy tuning in reinforcement learning for quadcopter control. They compared stochastic policies, which optimize a probability distribution over actions, against det…
-
Reinforcement learning controls twin rotor system effectively
Researchers have developed a reinforcement learning framework to control and stabilize a Twin Rotor Aerodynamic System (TRAS). The Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm was employed due to its …