102 citations · 144 across the 9 of their papers we have counts for
3 papers · 1 filter
Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
Ruiqi Zhang, Jing Hou, Florian Walter +7
Reinforcement Learning (RL) is a potent tool for sequential decision-making and has achieved performance surpassing human capabilities across many challenging real-world tasks. As…
A Review of Safe Reinforcement Learning: Methods, Theory and Applications
Shangding Gu, Long Yang, Yali Du +4
Reinforcement Learning (RL) has achieved tremendous success in many complex decision-making tasks. However, safety concerns are raised during deploying RL in real-world application…
Multi-Agent Constrained Policy Optimisation
Shangding Gu, Jakub Grudzien Kuba, Munning Wen +6
Developing reinforcement learning algorithms that satisfy safety constraints is becoming increasingly important in real-world applications. In multi-agent reinforcement learning (M…