# A Note on Stability in Asynchronous Stochastic Approximation without Communication Delays

arXiv: https://arxiv.org/abs/2312.15091 · HTML: https://mlsanity.com/paper/2312.15091/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 15 references that are in the map.
- First posted on arXiv 22 Dec 2023.

## Built on by (most cited first, 1 of 1)

- [On Convergence of Average-Reward Q-Learning in Weakly Communicating Markov Decision Processes](https://mlsanity.com/paper/2408.16262/) (2024)

## Abstract (arXiv)

In this paper, we study asynchronous stochastic approximation algorithms without communication delays. Our main contribution is a stability proof for these algorithms that extends a method of Borkar and Meyn by accommodating more general noise conditions. We also derive convergence results from this stability result and discuss their application in important average-reward reinforcement learning problems.