research
∙
03/16/2023
Goal-conditioned Offline Reinforcement Learning through State Space Partitioning
Offline reinforcement learning (RL) aims to infer sequential decision po...
share
research
∙
02/18/2023
Promoting Cooperation in Multi-Agent Reinforcement Learning via Mutual Help
Multi-agent reinforcement learning (MARL) has achieved great progress in...
research
∙
09/17/2022
Sample-Efficient Multi-Agent Reinforcement Learning with Demonstrations for Flocking Control
Flocking control is a significant problem in multi-agent systems such as...
research
∙
09/17/2022
Sub-optimal Policy Aided Multi-Agent Reinforcement Learning for Flocking Control
Flocking control is a challenging problem, where multiple agents, such a...
research
∙
05/23/2022
Learning to Advise and Learning from Advice in Cooperative Multi-Agent Reinforcement Learning
Learning to coordinate is a daunting problem in multi-agent reinforcemen...
research
∙
09/29/2021
Information-Bottleneck-Based Behavior Representation Learning for Multi-agent Reinforcement learning
In multi-agent deep reinforcement learning, extracting sufficient and co...
research
∙
07/09/2021
A Multi-modal and Multi-task Learning Method for Action Unit and Expression Recognition
Analyzing human affect is vital for human-computer interaction systems. ...
research
∙
07/03/2021
Supervised Off-Policy Ranking
Off-policy evaluation (OPE) leverages data generated by other policies t...
research
∙
08/11/2020
