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cs.LG2024
State-free Reinforcement Learning
Mingyu Chen, Aldo Pacchiano, Xuezhou Zhang
In this work, we study the \textit{state-free RL} problem, where the algorithm does not have the states information before interacting with the environment. Specifically, denote th…
eess.SY2024
Koopman-based Deep Learning for Nonlinear System Estimation
Zexin Sun, Mingyu Chen, John Baillieul
Nonlinear differential equations are encountered as models of fluid flow, spiking neurons, and many other systems of interest in the real world. Common features of these systems ar…
cs.LG2024
Scale-free Adversarial Reinforcement Learning
Mingyu Chen, Xuezhou Zhang
This paper initiates the study of scale-free learning in Markov Decision Processes (MDPs), where the scale of rewards/losses is unknown to the learner. We design a generic algorith…