42 citations · 63 across the 11 of their papers we have counts for
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cs.LG2020
Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime
Andrea Agazzi, Jianfeng Lu
We study the problem of policy optimization for infinite-horizon discounted Markov Decision Processes with softmax policy and nonlinear function approximation trained with policy g…
cs.LG2019★ 3 cited
Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes
Andrea Agazzi, Jianfeng Lu
We discuss the approximation of the value function for infinite-horizon discounted Markov Reward Processes (MRP) with nonlinear functions trained with the Temporal-Difference (TD)…