Paused Agent Replay Refresh

Reinforcement learning algorithms have become more complex since the invention of target networks. Unfortunately, target networks have not kept up with this increased complexity, instead requiring approximate solutions to be computationally feasible. These approximations increase noise in the Q-valu...

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Veröffentlicht in:	arXiv.org 2022-09
1. Verfasser:	Parr, Benjamin
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Approximation Complexity Computer architecture Machine learning Networks Sampling
Online-Zugang:	Volltext
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