DRIBO: Robust Deep Reinforcement Learning via Multi-View Information Bottleneck

Deep reinforcement learning (DRL) agents are often sensitive to visual changes that were unseen in their training environments. To address this problem, we leverage the sequential nature of RL to learn robust representations that encode only task-relevant information from observations based on the u...

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Veröffentlicht in:	arXiv.org 2022-07
Hauptverfasser:	Fan, Jiameng, Li, Wenchao
Format:	Artikel
Sprache:	eng
Schlagworte:	Control tasks Deep learning Representations Robustness Visual control Visual tasks
Online-Zugang:	Volltext
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