7 citations · 28 across the 43 of their papers we have counts for
6 papers · 1 filter
A Dual-Agent Adversarial Framework for Robust Generalization in Deep Reinforcement Learning
Zhengpeng Xie, Yulong Zhang
Recently, empowered with the powerful capabilities of neural networks, reinforcement learning (RL) has successfully tackled numerous challenging tasks. However, while these models…
Representation Convergence: Mutual Distillation is Secretly a Form of Regularization
Zhengpeng Xie, Jiahang Cao, Changwei Wang +5
In this paper, we argue that mutual distillation between reinforcement learning policies serves as an implicit regularization, preventing them from overfitting to irrelevant featur…
Mamba as Decision Maker: Exploring Multi-scale Sequence Modeling in Offline Reinforcement Learning
Jiahang Cao, Qiang Zhang, Ziqing Wang +8
Sequential modeling has demonstrated remarkable capabilities in offline reinforcement learning (RL), with Decision Transformer (DT) being one of the most notable representatives, a…
Self-Motivated Multi-Agent Exploration
Shaowei Zhang, Jiahan Cao, Lei Yuan +2
In cooperative multi-agent reinforcement learning (CMARL), it is critical for agents to achieve a balance between self-exploration and team collaboration. However, agents can hardl…
Knowledge Graph Embedding: A Survey from the Perspective of Representation Spaces
Jiahang Cao, Jinyuan Fang, Zaiqiao Meng +1
Knowledge graph embedding (KGE) is an increasingly popular technique that aims to represent entities and relations of knowledge graphs into low-dimensional semantic spaces for a wi…
LINDA: Multi-Agent Local Information Decomposition for Awareness of Teammates
Jiahan Cao, Lei Yuan, Jianhao Wang +4
In cooperative multi-agent reinforcement learning (MARL), where agents only have access to partial observations, efficiently leveraging local information is critical. During long-t…