From the 1 of 5 linked papers with an AI index.
5 papers
FedTopo: Relation-Level Topology Sharing for Model-Heterogeneous Federated Learning
Zhaoyang Ma, Zhihao Wu, Xin Gao +3
FedTopo introduces a method for federated learning with heterogeneous client models that shares class relation topologies instead of raw model parameters, enabling more reliable kn…
Learning social norms enhances compatibility in dynamic human-AI coordination
Yi Yang, Siyuan Liu, Xin Gao +4
Humans continuously coordinate with others in dynamic interactions, often through implicit, hard-to-quantify social norms that act as shared tacit expectations among interacting ag…
MAGE: Multi-scale Autoregressive Generation for Offline Reinforcement Learning
Chenxing Lin, Xinhui Gao, Haipeng Zhang +7
Generative models have gained significant traction in offline reinforcement learning (RL) due to their ability to model complex trajectory distributions. However, existing generati…
Red-Team Multi-Agent Reinforcement Learning for Emergency Braking Scenario
Yinsong Chen, Kaifeng Wang, Xiaoqiang Meng +3
Current research on decision-making in safety-critical scenarios often relies on inefficient data-driven scenario generation or specific modeling approaches, which fail to capture…
Dynamic Residual Safe Reinforcement Learning for Multi-Agent Safety-Critical Scenarios Decision-Making
Kaifeng Wang, Yinsong Chen, Qi Liu +2
In multi-agent safety-critical scenarios, traditional autonomous driving frameworks face significant challenges in balancing safety constraints and task performance. These framewor…