Breaking the deadly triad with a target network

Breaking the deadly triad with a target network

The deadly triad refers to the instability of a reinforcement learning algorithm when it employs off-policy learning, function approximation, and bootstrapping simultaneously. In this paper, we investigate the target network as a tool for breaking the deadly triad, providing theoretical support for...

Полное описание

Библиографические подробности
Главные авторы:	Zhang, S, Yao, H, Whiteson, S
Формат:	Conference item
Язык:	English
Опубликовано:	PMLR 2021

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