StyleAug: Style Augmentation for Multi-Agent Reinforcement Learning with Heterogeneous Observations

^*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Original language	English
Title of host publication	2025 International Conference on Computer, Internet of Things and Smart City (CIoTSC)
Publisher	IEEE
ISBN (Electronic)	979-8-3315-5522-1
ISBN (Print)	979-8-3315-5523-8
DOIs	https://doi.org/10.1109/CIoTSC67482.2025.11413058
Publication status	Published - 3 Mar 2026

Access to Document

@inproceedings{00aa1a12be6a4c5f839da71a346be864,

title = "StyleAug: Style Augmentation for Multi-Agent Reinforcement Learning with Heterogeneous Observations",

author = "Xueyan Yao and Yuji Dong and Matilda Isaac",

year = "2026",

month = mar,

day = "3",

doi = "10.1109/CIoTSC67482.2025.11413058",

language = "English",

isbn = "979-8-3315-5523-8",

booktitle = "2025 International Conference on Computer, Internet of Things and Smart City (CIoTSC)",

publisher = "IEEE",

}

TY - GEN

T1 - StyleAug: Style Augmentation for Multi-Agent Reinforcement Learning with Heterogeneous Observations

AU - Yao, Xueyan

AU - Dong, Yuji

AU - Isaac, Matilda

PY - 2026/3/3

Y1 - 2026/3/3

U2 - 10.1109/CIoTSC67482.2025.11413058

DO - 10.1109/CIoTSC67482.2025.11413058

M3 - Conference Proceeding

SN - 979-8-3315-5523-8

BT - 2025 International Conference on Computer, Internet of Things and Smart City (CIoTSC)

PB - IEEE

ER -