תאוריה סופית-מחזורית חד-פליית ללמידת תורשה קטגורית-הפיכה-זמנית

תקציר מקורי באנגליתarXiv:2605.06866v3 Announce Type: replace Abstract: We study finite-iteration behavior of asynchronous categorical distributional temporal-difference methods, covering scalar categorical TD (CTD) in the Cram\'er geometry and multivariate signed-categorical TD (MTD) in the maximum mean discrepancy (MMD) geometry. We establish high-probability guarantees under i.i.d. sampling and under a continuing Markovian trajectory. For CTD, the Cram\'er sample complexity to the true return law has leading term $\tilde O(\rho_{\min}^{-1}(1-\gamma)^{-2}\varepsilon^{-2})$ in the i.i.d. and $\tilde O(\mu_{\min}^{-1}(1-\gamma)^{-2}\varepsilon^{-2}+\mu_{\min}^{-1}t_{\mathrm{mix}})$ in the Markovian setting, without using variance reduction or data dropping. For MTD, the MMD sample complexity has leading terms