59 citations · 194 across the 18 of their papers we have counts for
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stat.ML2013
Model-Based Policy Gradients with Parameter-Based Exploration by Least-Squares Conditional Density Estimation
Syogo Mori, Voot Tangkaratt, Tingting Zhao +2
The goal of reinforcement learning (RL) is to let an agent learn an optimal control policy in an unknown environment so that future expected rewards are maximized. The model-free R…
cs.LG2013
Efficient Sample Reuse in Policy Gradients with Parameter-based Exploration
Tingting Zhao, Hirotaka Hachiya, Voot Tangkaratt +2
The policy gradient approach is a flexible and powerful reinforcement learning method particularly for problems with continuous actions such as robot control. A common challenge in…