19 citations · 88 across the 27 of their papers we have counts for
4 papers · 1 filter
Safe Driving via Expert Guided Policy Optimization
Zhenghao Peng, Quanyi Li, Chunxiao Liu +1
When learning common skills like driving, beginners usually have domain experts standing by to ensure the safety of the learning process. We formulate such learning scheme under th…
Learning to Simulate Self-Driven Particles System with Coordinated Policy Optimization
Zhenghao Peng, Quanyi Li, Ka Ming Hui +2
Self-Driven Particles (SDP) describe a category of multi-agent systems common in everyday life, such as flocking birds and traffic flows. In a SDP system, each agent pursues its ow…
MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning
Quanyi Li, Zhenghao Peng, Lan Feng +3
Driving safely requires multiple capabilities from human and intelligent agents, such as the generalizability to unseen environments, the safety awareness of the surrounding traffi…
Safe Exploration by Solving Early Terminated MDP
Hao Sun, Ziping Xu, Meng Fang +4
Safe exploration is crucial for the real-world application of reinforcement learning (RL). Previous works consider the safe exploration problem as Constrained Markov Decision Proce…