53 citations · 53 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Adapting Double Q-Learning for Continuous Reinforcement Learning
Arsenii Kuznetsov
Majority of off-policy reinforcement learning algorithms use overestimation bias control techniques. Most of these techniques rooted in heuristics, primarily addressing the consequ…
cs.LG2021
Automating Control of Overestimation Bias for Reinforcement Learning
Arsenii Kuznetsov, Alexander Grishin, Artem Tsypin +3
Overestimation bias control techniques are used by the majority of high-performing off-policy reinforcement learning algorithms. However, most of these techniques rely on pre-defin…
cs.LG2020★ 53 cited
Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics
Arsenii Kuznetsov, Pavel Shvechikov, Alexander Grishin +1
The overestimation bias is one of the major impediments to accurate off-policy learning. This paper investigates a novel way to alleviate the overestimation bias in a continuous co…