177 citations · 995 across the 65 of their papers we have counts for
12 papers · 1 filter
Models as Agents: Optimizing Multi-Step Predictions of Interactive Local Models in Model-Based Multi-Agent Reinforcement Learning
Zifan Wu, Chao Yu, Chen Chen +2
Research in model-based reinforcement learning has made significant progress in recent years. Compared to single-agent settings, the exponential dimension growth of the joint state…
Off-Beat Multi-Agent Reinforcement Learning
Wei Qiu, Weixun Wang, Rundong Wang +7
We investigate model-free multi-agent reinforcement learning (MARL) in environments where off-beat actions are prevalent, i.e., all actions have pre-set execution durations. During…
SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving
Ming Zhou, Jun Luo, Julian Villella +34
Multi-agent interaction is a fundamental aspect of autonomous driving in the real world. Despite more than a decade of research and development, the problem of how to competently i…
Event-Triggered Multi-agent Reinforcement Learning with Communication under Limited-bandwidth Constraint
Guangzheng Hu, Yuanheng Zhu, Dongbin Zhao +2
Communicating with each other in a distributed manner and behaving as a group are essential in multi-agent reinforcement learning. However, real-world multi-agent systems suffer fr…
Q-value Path Decomposition for Deep Multiagent Reinforcement Learning
Yaodong Yang, Jianye Hao, Guangyong Chen +5
Recently, deep multiagent reinforcement learning (MARL) has become a highly active research area as many real-world problems can be inherently viewed as multiagent systems. A parti…
Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning
Yaodong Yang, Jianye Hao, Ben Liao +4
In many real-world tasks, multiple agents must learn to coordinate with each other given their private observations and limited communication ability. Deep multiagent reinforcement…
Independent Generative Adversarial Self-Imitation Learning in Cooperative Multiagent Systems
Xiaotian Hao, Weixun Wang, Jianye Hao +1
Many tasks in practice require the collaboration of multiple agents through reinforcement learning. In general, cooperative multiagent reinforcement learning algorithms can be clas…
Action Semantics Network: Considering the Effects of Actions in Multiagent Systems
Weixun Wang, Tianpei Yang, Yong Liu +6
In multiagent systems (MASs), each agent makes individual decisions but all of them contribute globally to the system evolution. Learning in MASs is difficult since each agent's se…
Towards Efficient Detection and Optimal Response against Sophisticated Opponents
Tianpei Yang, Zhaopeng Meng, Jianye Hao +3
Multiagent algorithms often aim to accurately predict the behaviors of other agents and find a best response accordingly. Previous works usually assume an opponent uses a stationar…
An Optimal Rewiring Strategy for Reinforcement Social Learning in Cooperative Multiagent Systems
Hongyao Tang, Li Wang, Zan Wang +2
Multiagent coordination in cooperative multiagent systems (MASs) has been widely studied in both fixed-agent repeated interaction setting and the static social learning framework.…
Hierarchical Heuristic Learning towards Effcient Norm Emergence
Tianpei Yang, Jianye Hao, Zhaopeng Meng +2
Social norms serve as an important mechanism to regulate the behaviors of agents and to facilitate coordination among them in multiagent systems. One important research question is…
Weighted Double Deep Multiagent Reinforcement Learning in Stochastic Cooperative Environments
Yan Zheng, Jianye Hao, Zongzhang Zhang
Recently, multiagent deep reinforcement learning (DRL) has received increasingly wide attention. Existing multiagent DRL algorithms are inefficient when facing with the non-station…