13 citations · 22 across the 3 of their papers we have counts for
3 papers
cs.AI2023★ 8 cited
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance
Yuchen Fang, Zhenggang Tang, Kan Ren +7
Order execution is a fundamental task in quantitative finance, aiming at finishing acquisition or liquidation for a number of trading orders of the specific assets. Recent advance…
cs.LG2021★ 1 cited
A Microscopic Pandemic Simulator for Pandemic Prediction Using Scalable Million-Agent Reinforcement Learning
Zhenggang Tang, Kai Yan, Liting Sun +2
Microscopic epidemic models are powerful tools for government policy makers to predict and simulate epidemic outbreaks, which can capture the impact of individual behaviors on the…
cs.AI2021★ 13 cited
Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization
Zhenggang Tang, Chao Yu, Boyuan Chen +6
We propose a simple, general and effective technique, Reward Randomization for discovering diverse strategic policies in complex multi-agent games. Combining reward randomization a…