1 citations · 1 across the 2 of their papers we have counts for
2 papers
q-fin.TR2024★ 1 cited
Reinforcement Learning in Agent-Based Market Simulation: Unveiling Realistic Stylized Facts and Behavior
Zhiyuan Yao, Zheng Li, Matthew Thomas +1
Investors and regulators can greatly benefit from a realistic market simulator that enables them to anticipate the consequences of their decisions in real markets. However, traditi…
cs.LG2024
Control in Stochastic Environment with Delays: A Model-based Reinforcement Learning Approach
Zhiyuan Yao, Ionut Florescu, Chihoon Lee
In this paper we are introducing a new reinforcement learning method for control problems in environments with delayed feedback. Specifically, our method employs stochastic plannin…