2 papers
cs.LG2025
Asynchronous Policy Gradient Aggregation for Efficient Distributed Reinforcement Learning
Alexander Tyurin, Andrei Spiridonov, Varvara Rudenko
We study distributed reinforcement learning (RL) with policy gradient methods under asynchronous and parallel computations and communications. While non-distributed methods are wel…
math.OC2022
Algorithm for Constrained Markov Decision Process with Linear Convergence
Egor Gladin, Maksim Lavrik-Karmazin, Karina Zainullina +3
The problem of constrained Markov decision process is considered. An agent aims to maximize the expected accumulated discounted reward subject to multiple constraints on its costs…