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cs.LG2019
Efficient decorrelation of features using Gramian in Reinforcement Learning
Borislav Mavrin, Daniel Graves, Alan Chan
Learning good representations is a long standing problem in reinforcement learning (RL). One of the conventional ways to achieve this goal in the supervised setting is through regu…
cs.LG2019
Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning
Kristopher De Asis, Alan Chan, Silviu Pitis +2
We explore fixed-horizon temporal difference (TD) methods, reinforcement learning algorithms for a new kind of value function that predicts the sum of rewards over a $\textit{fixed…