We investigate model-free multi-agent reinforcement learning (MARL) in
e...
Advantage Actor-critic (A2C) and Proximal Policy Optimization (PPO) are
...
Multi-agent reinforcement learning is difficult to be applied in practic...
In cooperative multi-agent systems, agents jointly take actions and rece...
Extending transfer learning to cooperative multi-agent reinforcement lea...
Bipartite b-matching is fundamental in algorithm design, and has been wi...
Transfer Learning (TL) has shown great potential to accelerate Reinforce...
Transfer Learning has shown great potential to enhance the single-agent
...
Reinforcement learning agents usually learn from scratch, which requires...
Many tasks in practice require the collaboration of multiple agents thro...
A lot of efforts have been devoted to investigating how agents can learn...
In multiagent systems (MASs), each agent makes individual decisions but ...
For online advertising in e-commerce, the traditional problem is to assi...
The Iterated Prisoner's Dilemma has guided research on social dilemmas f...