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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 17Source ↗Scholar ↗
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 10Source ↗Scholar ↗