Selective imitation for efficient online reinforcement learning with pre-collected data

Selective imitation for efficient online reinforcement learning with pre-collected data

Deep reinforcement learning (RL) has emerged as a promising solution for autonomous devices requiring sequential decision-making. In the online RL framework, the agent must interact with the environment to collect data, making sample efficiency the most challenging aspect. While the off-policy metho...

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Bibliographic Details
Main Authors: Chanin Eom, Dongsu Lee, Minhae Kwon
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:ICT Express
Subjects:
Deep reinforcement learning
Off-policy reinforcement learning
Pre-collected data
Behavioral cloning
Imitation learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2405959524001048
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