A Note on Stability in Asynchronous Stochastic Approximation without Communication Delays
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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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 0 of its 15 references that are in the map. First posted on arXiv 22 Dec 2023.
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