Hybrid Attribution-Based Interpretable Deep Reinforcement Learning for Autonomous Driving Behavior Decision-Making

With the increasing deployment of autonomous driving systems, the opaque nature of deep reinforcement learning (DRL) decision models hinders understanding and validation of driving decisions. To address this challenge, we propose a Hybrid Attribution-based Interpretable Deep Reinforcement Learning f...

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Hlavní autoři:	Yaxuan Liu, Jiakun Huang, Mingjun Li, Qing Ye, Xiaolin Song
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2026-03-01
Edice:	Applied Sciences
Témata:	autonomous driving behavior decision-making interpretable reinforcement learning hybrid attribution dueling DQN
On-line přístup:	https://www.mdpi.com/2076-3417/16/6/3096
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