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Cong Qiu

2 accepted papers

2022

Cola-HRL: Continuous-Lattice Hierarchical Reinforcement Learning for Autonomous Driving

IROS 2022poster

Reinforcement learning (RL) has shown promising performance in autonomous driving applications in recent years. The early end-to-end RL method is usually unexplainable and fails to generate stable actions, while the hierarchical RL (HRL) method can tackle the above issues by dividing complex problem…

Cited by 17SourceScholar
2021

KB-Tree: Learnable and Continuous Monte-Carlo Tree Search for Autonomous Driving Planning

IROS 2021poster

In this paper, we present a novel learnable and continuous Monte-Carlo Tree Search method, named as KB-Tree, for motion planning in autonomous driving. The proposed method utilizes an asymptotical PUCB based on Kernel Regression (KR-AUCB) as a novel UCB variant, to improve the exploitation and explo…

Cited by 10SourceScholar