Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces

arXiv:2406.11281v1 Announce Type: cross
Abstract: We explore the control of stochastic systems with potentially continuous state and action spaces, characterized by the state dynamics $X_{t+1} = f(X_t, A_t, W_t)$. Here, $X$, $A$, and $W$ represent the state, action, and exogenous random noise processes, respectively, with $f$ denoting a known function that describes state transitions. Traditionally, the noise process $\{W_t, t \geq 0\}$ is assumed to be independent and identically distributed, with a distribution that is either fully known or can …

abstract action arxiv continuous control cs.lg dynamics exogenous explore noise processes random robust spaces state statistical stat.ml stochastic systems type