Towards Understanding Asynchronous Advantage Actor-critic: Convergence
and Linear Speedup

Towards Understanding Asynchronous Advantage Actor-critic: Convergence and Linear Speedup

31 December 2020

Tianyi Chen

Papers citing "Towards Understanding Asynchronous Advantage Actor-critic: Convergence and Linear Speedup"

7 / 7 papers shown

Title
Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation under Markovian Sampling Feng Zhu Aritra Mitra Robert W. Heath FedML 36 0 0 15 Apr 2025
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis Guangchen Lan Dong-Jun Han Abolfazl Hashemi Vaneet Aggarwal Christopher G. Brinton 124 15 0 09 Apr 2024
CAESAR: Enhancing Federated RL in Heterogeneous MDPs through Convergence-Aware Sampling with Screening Hei Yi Mak Flint Xiaofeng Fan Luca A. Lanzendörfer Cheston Tan Wei Tsang Ooi Roger Wattenhofer FedML 24 2 0 29 Mar 2024
Distributed TD(0) with Almost No Communication R. Liu Alexander Olshevsky FedML 15 14 0 16 Apr 2021
On Linear Convergence of Policy Gradient Methods for Finite MDPs Jalaj Bhandari Daniel Russo 55 59 0 21 Jul 2020
A Finite Time Analysis of Two Time-Scale Actor Critic Methods Yue Wu Weitong Zhang Pan Xu Quanquan Gu 90 145 0 04 May 2020
On the Sample Complexity of Actor-Critic Method for Reinforcement Learning with Function Approximation Harshat Kumar Alec Koppel Alejandro Ribeiro 99 79 0 18 Oct 2019