51 citations · 233 across the 19 of their papers we have counts for
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cs.LG2015★ 24 cited
Weak Convergence Properties of Constrained Emphatic Temporal-difference Learning with Constant and Slowly Diminishing Stepsize
Huizhen Yu
We consider the emphatic temporal-difference (TD) algorithm, ETD(), for learning the value functions of stationary policies in a discounted, finite state and action Markov decis…
cs.LG2015★ 21 cited
Emphatic Temporal-Difference Learning
A. Rupam Mahmood, Huizhen Yu, Martha White +1
Emphatic algorithms are temporal-difference learning algorithms that change their effective state distribution by selectively emphasizing and de-emphasizing their updates on differ…
cs.LG2015★ 51 cited
On Convergence of Emphatic Temporal-Difference Learning
Huizhen Yu
We consider emphatic temporal-difference learning algorithms for policy evaluation in discounted Markov decision processes with finite spaces. Such algorithms were recently propose…