AM Devraj, S Meyn - Advances in Neural Information …, 2017 - proceedings.neurips.cc
The Zap Q-learning algorithm introduced in this paper is an improvement of Watkins' original algorithm and recent competitors in several respects. It is a matrix-gain algorithm designed …
P Karmakar, S Bhatnagar - Mathematics of Operations …, 2018 - pubsonline.informs.org
We present for the first time an asymptotic convergence analysis of two time-scale stochastic approximation driven by “controlled” Markov noise. In particular, the faster and slower …
T Rydén - Stochastic Processes and their Applications, 1997 - Elsevier
Hidden Markov models (HMMs) have during the last decade become a widespread tool for modelling sequences of dependent random variables. In this paper we consider a recursive …
X Li, J Liang, Z Zhang - arXiv preprint arXiv:2302.07690, 2023 - arxiv.org
We study the statistical inference of nonlinear stochastic approximation algorithms utilizing a single trajectory of Markovian data. Our methodology has practical applications in various …
Along with the sharp increase in visibility of the field, the rate at which new reinforcement learning algorithms are being proposed is at a new peak. While the surge in activity is …
The Zap Q-learning algorithm introduced in this paper is an improvement of Watkins' original algorithm and recent competitors in several respects. It is a matrix-gain algorithm designed …
J Chakravorty, A Mahajan - 2016 Information Theory and …, 2016 - ieeexplore.ieee.org
The fundamental limits of remote estimation of autoregressive Markov processes under communication constraints are presented. The remote estimation system consists of a …
A Cartea, P Chang, J Penalva… - Available at SSRN …, 2022 - papers.ssrn.com
We introduce the algorithmic learning equations, a set of ordinary differential equations which characterizes the finite-time and asymptotic behavior of the stochastic interaction …
S Perkins, DS Leslie - Stochastic Systems, 2013 - pubsonline.informs.org
The asymptotic pseudo-trajectory approach to stochastic approximation of Benaïm, Hofbauer and Sorin is extended for asynchronous stochastic approximations with a set …