most citedLearning Practical Communication Strategies in Cooperative Multi-Agent Reinforcement Learning

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.GN20241 cited

dnaGrinder: a lightweight and high-capacity genomic foundation model

Qihang Zhao, Chi Zhang, Weixiong Zhang

The task of understanding and interpreting the complex information encoded within genomic sequences remains a grand challenge in biological research and clinical applications. In t…

cs.DC2024

A 1024 RV-Cores Shared-L1 Cluster with High Bandwidth Memory Link for Low-Latency 6G-SDR

Yichao Zhang, Marco Bertuletti, Chi Zhang +3

We introduce an open-source architecture for next-generation Radio-Access Network baseband processing: 1024 latency-tolerant 32-bit RISC-V cores share 4 MiB of L1 memory via an ult…

cond-mat.quant-gas2024

Observation of the antiferromagnetic phase transition in the fermionic Hubbard model

Hou-Ji Shao, Yu-Xuan Wang, De-Zhi Zhu +9

The fermionic Hubbard model (FHM)[1], despite its simple form, captures essential features of strongly correlated electron physics. Ultracold fermions in optical lattices[2, 3] pro…

cs.CV2024

Stream Query Denoising for Vectorized HD Map Construction

Shuo Wang, Fan Jia, Yingfei Liu +6

To enhance perception performance in complex and extensive scenarios within the realm of autonomous driving, there has been a noteworthy focus on temporal modeling, with a particul…

cs.AI20221 cited

Learning Practical Communication Strategies in Cooperative Multi-Agent Reinforcement Learning

Diyi Hu, Chi Zhang, Viktor Prasanna +1

In Multi-Agent Reinforcement Learning, communication is critical to encourage cooperation among agents. Communication in realistic wireless networks can be highly unreliable due to…