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Context-Aware Safe Reinforcement Learning for Non-Stationary Environments


Jan 02, 2021
Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Ding Zhao


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Safe Model-based Reinforcement Learning with Robust Cross-Entropy Method


Oct 15, 2020
Zuxin Liu, Hongyi Zhou, Baiming Chen, Sicheng Zhong, Martial Hebert, Ding Zhao

* 9 pages, 6 figures 

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Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation


Sep 25, 2020
Wenhao Ding, Baiming Chen, Bo Li, Kim Ji Eun, Ding Zhao

* 8 pages, 7 figures 

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MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments


Jul 30, 2020
Zuxin Liu, Baiming Chen, Hongyi Zhou, Guru Koushik, Martial Hebert, Ding Zhao

* 6 pages, accepted at the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020) 

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Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes


Jun 29, 2020
Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao

* 16 pages, 6 figures 

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Delay-Aware Multi-Agent Reinforcement Learning


May 11, 2020
Baiming Chen, Mengdi Xu, Zuxin Liu, Liang Li, Ding Zhao


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Delay-Aware Model-Based Reinforcement Learning for Continuous Control


May 11, 2020
Baiming Chen, Mengdi Xu, Liang Li, Ding Zhao


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Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios


Apr 14, 2020
Baiming Chen, Liang Li


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Evaluation of Automated Vehicles Encountering Pedestrians at Unsignalized Crossings


Mar 28, 2017
Baiming Chen, Ding Zhao, Huei Peng


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