2 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 2 cited
Boosting Exploration in Actor-Critic Algorithms by Incentivizing Plausible Novel States
Chayan Banerjee, Zhiyong Chen, Nasimul Noman
Actor-critic (AC) algorithms are a class of model-free deep reinforcement learning algorithms, which have proven their efficacy in diverse domains, especially in solving continuous…
cs.LG2021★ 2 cited
Improved Soft Actor-Critic: Mixing Prioritized Off-Policy Samples with On-Policy Experience
Chayan Banerjee, Zhiyong Chen, Nasimul Noman
Soft Actor-Critic (SAC) is an off-policy actor-critic reinforcement learning algorithm, essentially based on entropy regularization. SAC trains a policy by maximizing the trade-off…
cs.LG2021
Optimal Actor-Critic Policy with Optimized Training Datasets
Chayan Banerjee, Zhiyong Chen, Nasimul Noman +1
Actor-critic (AC) algorithms are known for their efficacy and high performance in solving reinforcement learning problems, but they also suffer from low sampling efficiency. An AC…