Offline reinforcement learning (RL) aims to infer sequential decision
po...
Multi-agent reinforcement learning (MARL) has achieved great progress in...
Flocking control is a significant problem in multi-agent systems such as...
Flocking control is a challenging problem, where multiple agents, such a...
Learning to coordinate is a daunting problem in multi-agent reinforcemen...
In multi-agent deep reinforcement learning, extracting sufficient and co...
Analyzing human affect is vital for human-computer interaction systems. ...
Off-policy evaluation (OPE) leverages data generated by other policies t...
Accelerating deep model training and inference is crucial in practice.
E...