Understanding What Affects the Generalization Gap in Visual Reinforcement Learning: Theory and Empirical Evidence

Recently, there are many efforts attempting to learn useful policies for continuous control in visual reinforcement learning (RL). In this scenario, it is important to learn a generalizable policy, as the testing environment may differ from the training environment, e.g., there exist distractors dur...

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Bibliographic Details
Published in:The Journal of artificial intelligence research Vol. 81; pp. 1 - 42
Main Authors: Lyu, Jiafei, Wan, Le, Li, Xiu, Lu, Zongqing
Format: Journal Article
Language:English
Published: San Francisco AI Access Foundation 2024
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ISSN:1076-9757, 1076-9757, 1943-5037
Online Access:Get full text
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