1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 1 cited
Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow
John McLeod, Hrvoje Stojic, Vincent Adam +4
In the past decade, model-free reinforcement learning (RL) has provided solutions to challenging domains such as robotics. Model-based RL shows the prospect of being more sample-ef…
cs.LG2019
Policy Optimization Through Approximate Importance Sampling
Marcin B. Tomczak, Dongho Kim, Peter Vrancx +1
Recent policy optimization approaches (Schulman et al., 2015a; 2017) have achieved substantial empirical successes by constructing new proxy optimization objectives. These proxy ob…