In this paper, we provide a finite-time analysis of the fully decentralized TD(0) learning under both iid as well as Markovian samples.
Jun 6, 2018 · In this work, we provide a simple and explicit finite time analysis of temporal difference learning with linear function approximation.
Missing: Decentralized | Show results with:Decentralized
By exploring the asymptotic behavior, TD(0) learning with linear function approximation can be viewed as a discretized version of an ordinary differential ...
Mar 19, 2021 · In this work, we provide a simple and explicit finite time analysis of temporal difference learning with linear function approximation.
Finite-Time Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation. Proceedings of Machine Learning Research, 108, 4485-4495.
As an accelerated version of TD, the adaptive TD has been proposed and proved to enjoy finite-time convergence under the linear function approximation. Existing ...
Oct 12, 2022 · We study the finite-time behaviour of the popular temporal difference (TD) learning algorithm when combined with tail-averaging.
Missing: Decentralized | Show results with:Decentralized
Temporal difference learning (TD) is a simple iterative algorithm widely used for policy evaluation in Markov reward processes. Bhandari et al. prove finite ...
Nov 23, 2023 · This paper studies the federated RL problem, and designs a HFTD algorithm for federated TD learning with linear function approximation under ...
In this work, we provide a simple and explicit finite time analysis of temporal difference learning with linear function approximation. Except for a few key ...
Missing: Decentralized | Show results with:Decentralized