ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2202.00150
  4. Cited By
Learning Infinite-Horizon Average-Reward Markov Decision Processes with
  Constraints

Learning Infinite-Horizon Average-Reward Markov Decision Processes with Constraints

31 January 2022
Liyu Chen
R. Jain
Haipeng Luo
ArXivPDFHTML

Papers citing "Learning Infinite-Horizon Average-Reward Markov Decision Processes with Constraints"

19 / 19 papers shown
Title
Efficient Exploration in Average-Reward Constrained Reinforcement
  Learning: Achieving Near-Optimal Regret With Posterior Sampling
Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling
Danil Provodin
M. Kaptein
Mykola Pechenizkiy
39
0
0
29 May 2024
Online Restless Multi-Armed Bandits with Long-Term Fairness Constraints
Online Restless Multi-Armed Bandits with Long-Term Fairness Constraints
Shu-Fan Wang
Guojun Xiong
Jian Li
51
6
0
16 Dec 2023
Provably Efficient Exploration in Constrained Reinforcement
  Learning:Posterior Sampling Is All You Need
Provably Efficient Exploration in Constrained Reinforcement Learning:Posterior Sampling Is All You Need
Danil Provodin
Pratik Gajane
Mykola Pechenizkiy
M. Kaptein
31
0
0
27 Sep 2023
Model-Free, Regret-Optimal Best Policy Identification in Online CMDPs
Model-Free, Regret-Optimal Best Policy Identification in Online CMDPs
Zihan Zhou
Honghao Wei
Lei Ying
OffRL
40
1
0
27 Sep 2023
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon
  Average Reward Markov Decision Processes
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes
Qinbo Bai
Washim Uddin Mondal
Vaneet Aggarwal
26
9
0
05 Sep 2023
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for
  Constrained MDPs
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs
Dongsheng Ding
Chen-Yu Wei
Kaipeng Zhang
Alejandro Ribeiro
40
19
0
20 Jun 2023
Provably Efficient Generalized Lagrangian Policy Optimization for Safe
  Multi-Agent Reinforcement Learning
Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning
Dongsheng Ding
Xiaohan Wei
Zhuoran Yang
Zhaoran Wang
Mihailo R. Jovanović
OffRL
32
11
0
31 May 2023
Online Resource Allocation in Episodic Markov Decision Processes
Online Resource Allocation in Episodic Markov Decision Processes
Duksang Lee
William Overman
Dabeen Lee
37
1
0
18 May 2023
Model-Free Robust Average-Reward Reinforcement Learning
Model-Free Robust Average-Reward Reinforcement Learning
Yue Wang
Alvaro Velasquez
George K. Atia
Ashley Prater-Bennette
Shaofeng Zou
32
9
0
17 May 2023
Graph Exploration for Effective Multi-agent Q-Learning
Graph Exploration for Effective Multi-agent Q-Learning
Ainur Zhaikhan
Ali H. Sayed
37
1
0
19 Apr 2023
Provably Efficient Model-Free Algorithms for Non-stationary CMDPs
Provably Efficient Model-Free Algorithms for Non-stationary CMDPs
Honghao Wei
A. Ghosh
Ness B. Shroff
Lei Ying
Xingyu Zhou
11
13
0
10 Mar 2023
Online Nonstochastic Control with Adversarial and Static Constraints
Online Nonstochastic Control with Adversarial and Static Constraints
Xin Liu
Zixi Yang
Lei Ying
36
5
0
05 Feb 2023
ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints
ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints
Akhil Agnihotri
R. Jain
Haipeng Luo
21
2
0
02 Feb 2023
Safe Posterior Sampling for Constrained MDPs with Bounded Constraint
  Violation
Safe Posterior Sampling for Constrained MDPs with Bounded Constraint Violation
K. C. Kalagarla
Rahul Jain
Pierluigi Nuzzo
24
6
0
27 Jan 2023
Robust Average-Reward Markov Decision Processes
Robust Average-Reward Markov Decision Processes
Yue Wang
Alvaro Velasquez
George K. Atia
Ashley Prater-Bennette
Shaofeng Zou
33
11
0
02 Jan 2023
An Empirical Evaluation of Posterior Sampling for Constrained
  Reinforcement Learning
An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning
Danil Provodin
Pratik Gajane
Mykola Pechenizkiy
M. Kaptein
25
1
0
08 Sep 2022
Concave Utility Reinforcement Learning with Zero-Constraint Violations
Concave Utility Reinforcement Learning with Zero-Constraint Violations
Mridul Agarwal
Qinbo Bai
Vaneet Aggarwal
33
12
0
12 Sep 2021
Learning in Markov Decision Processes under Constraints
Learning in Markov Decision Processes under Constraints
Rahul Singh
Abhishek Gupta
Ness B. Shroff
33
27
0
27 Feb 2020
Model-free Reinforcement Learning in Infinite-horizon Average-reward
  Markov Decision Processes
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes
Chen-Yu Wei
Mehdi Jafarnia-Jahromi
Haipeng Luo
Hiteshi Sharma
R. Jain
107
99
0
15 Oct 2019
1