Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Sample complexity of asynchronous Q-learning: Sharper analysis and variance reduction
Asynchronous Q-learning aims to learn the optimal action-value function (or Q-function) of a
Markov decision process (MDP), based on a single trajectory of Markovian samples induced …
Markov decision process (MDP), based on a single trajectory of Markovian samples induced …
Sample complexity of asynchronous Q-learning: Sharper analysis and variance reduction
Asynchronous Q-learning aims to learn the optimal action-value function (or Q-function) of a
Markov decision process (MDP), based on a single trajectory of Markovian samples induced …
Markov decision process (MDP), based on a single trajectory of Markovian samples induced …
Characterizing the exact behaviors of temporal difference learning algorithms using Markov jump linear system theory
In this paper, we provide a unified analysis of temporal difference learning algorithms with
linear function approximators by exploiting their connections to Markov jump linear systems …
linear function approximators by exploiting their connections to Markov jump linear systems …
Finite-time performance of distributed temporal-difference learning with linear function approximation
We study the policy evaluation problem in multi-agent reinforcement learning, modeled by a
Markov decision process. In this problem, the agents operate in a common environment …
Markov decision process. In this problem, the agents operate in a common environment …
Reanalysis of variance reduced temporal difference learning
A unified switching system perspective and convergence analysis of Q-learning algorithms
This paper develops a novel and unified framework to analyze the convergence of a large
family of Q-learning algorithms from the switching system perspective. We show that the …
family of Q-learning algorithms from the switching system perspective. We show that the …
A multistep Lyapunov approach for finite-time analysis of biased stochastic approximation
Motivated by the widespread use of temporal-difference (TD-) and Q-learning algorithms in
reinforcement learning, this paper studies a class of biased stochastic approximation (SA) …
reinforcement learning, this paper studies a class of biased stochastic approximation (SA) …
Finite-time analysis and restarting scheme for linear two-time-scale stochastic approximation
TT Doan - SIAM Journal on Control and Optimization, 2021 - SIAM
Motivated by its broad applications in machine learning and reinforcement learning, we
study the linear two-time-scale stochastic approximation, an iterative method using two …
study the linear two-time-scale stochastic approximation, an iterative method using two …