Qu, Guannan and Wierman, Adam (2020) Finite-Time Analysis of Asynchronous Stochastic Approximation and Q-Learning. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20200214-105555380
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Abstract
We consider a general asynchronous Stochastic Approximation (SA) scheme featuring a weighted infinity-norm contractive operator, and prove a bound on its finite-time convergence rate on a single trajectory. Additionally, we specialize the result to asynchronous
| Item Type: | Report or Paper (Discussion Paper) | ||||||
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| Additional Information: | © 2020 G. Qu & A. Wierman. to appear in Proceedings of Machine Learning Research. | ||||||
| Subject Keywords: | Stochastic approximation, Q-learning, finite time analysis | ||||||
| Record Number: | CaltechAUTHORS:20200214-105555380 | ||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20200214-105555380 | ||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||
| ID Code: | 101300 | ||||||
| Collection: | CaltechAUTHORS | ||||||
| Deposited By: | George Porter | ||||||
| Deposited On: | 14 Feb 2020 21:04 | ||||||
| Last Modified: | 14 Feb 2020 21:04 |
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