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Huayou Su

2 accepted papers

2021

Graphcomm: A Graph Neural Network Based Method for Multi-Agent Reinforcement Learning

ICASSP 2021accepted

The communication among agents is important for Multi-Agent Reinforcement Learning (MARL). In this work, we propose GraphComm, a method makes use of the relation-ships among agents for MARL communication. GraphComm takes the explicit relations (e.g., agent types), which can be provided through some…

Cited by 0Source ↗Scholar ↗
2020

Learning Network Representation Through Reinforcement Learning

ICASSP 2020accepted

Network Representation Learning embeds each node in a network into a low-dimensional real-value vector which can be used for downstream tasks such as link prediction and recommendation. Many existing approaches use unsupervised or (semi-)supervised methods to explore the network topology and learn r…

Cited by 0Source ↗Scholar ↗