Cover Image

Federated Control in Markov Decision Processes

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jin, Hao, Peng, Yang, Zhang, Liangyu, Zhang, Zhihua
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Federated Reinforcement Learning with Constraint Heterogeneity
by: Jin, Hao, et al.
Published: (2024)

Statistical Efficiency of Distributional Temporal Difference Learning and Freedman's Inequality in Hilbert Spaces
by: Peng, Yang, et al.
Published: (2024)

A Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation
by: Peng, Yang, et al.
Published: (2025)

Estimation and Inference in Distributional Reinforcement Learning
by: Zhang, Liangyu, et al.
Published: (2023)

Generalized Linear Markov Decision Process
by: Zhang, Sinian, et al.
Published: (2025)

Improving Controller Generalization with Dimensionless Markov Decision Processes
by: Charvet, Valentin, et al.
Published: (2025)

Achieving Constant Regret in Linear Markov Decision Processes
by: Zhang, Weitong, et al.
Published: (2024)

Horizon-Free Regret for Linear Markov Decision Processes
by: Zhang, Zihan, et al.
Published: (2024)

Monitored Markov Decision Processes
by: Parisi, Simone, et al.
Published: (2024)

Interaction-Grounded Learning for Contextual Markov Decision Processes with Personalized Feedback
by: Zhang, Mengxiao, et al.
Published: (2026)

Increasing Information for Model Predictive Control with Semi-Markov Decision Processes
by: Hosseinkhan-Boucher, Rémy, et al.
Published: (2025)

Accelerated Distributional Temporal Difference Learning with Linear Function Approximation
by: Jin, Kaicheng, et al.
Published: (2025)

Transition Transfer $Q$-Learning for Composite Markov Decision Processes
by: Chai, Jinhang, et al.
Published: (2025)

Learning in Markov Decision Processes with Exogenous Dynamics
by: Maran, Davide, et al.
Published: (2026)

Act as You Learn: Adaptive Decision-Making in Non-Stationary Markov Decision Processes
by: Luo, Baiting, et al.
Published: (2024)

Weakly Time-Coupled Approximation of Markov Decision Processes
by: Soheili, Negar, et al.
Published: (2026)

Optimal Decision Tree Policies for Markov Decision Processes
by: Vos, Daniël, et al.
Published: (2023)

Policy Testing in Markov Decision Processes
by: Ariu, Kaito, et al.
Published: (2025)

Provably Efficient Reward Transfer in Reinforcement Learning with Discrete Markov Decision Processes
by: Vora, Kevin, et al.
Published: (2025)

Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes
by: Ye, Chenlu, et al.
Published: (2022)

Markov Decision Processes under External Temporal Processes
by: Ayyagari, Ranga Shaarad, et al.
Published: (2023)

Learning Utilities from Demonstrations in Markov Decision Processes
by: Lazzati, Filippo, et al.
Published: (2024)

The regret lower bound for communicating Markov Decision Processes
by: Boone, Victor, et al.
Published: (2025)

An Orthogonal Learner for Individualized Outcomes in Markov Decision Processes
by: Javurek, Emil, et al.
Published: (2025)

Initial Distribution Sensitivity of Constrained Markov Decision Processes
by: Tercan, Alperen, et al.
Published: (2025)

Model-Based Exploration in Monitored Markov Decision Processes
by: Kazemipour, Alireza, et al.
Published: (2025)

Concentration of Cumulative Reward in Markov Decision Processes
by: Sayedana, Borna, et al.
Published: (2024)

Policy Gradient for Robust Markov Decision Processes
by: Wang, Qiuhao, et al.
Published: (2024)

No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes
by: Bayrooti, Jasmine, et al.
Published: (2025)

Performance Improvement Bounds for Lipschitz Configurable Markov Decision Processes
by: Metelli, Alberto Maria
Published: (2024)

Transition Constrained Bayesian Optimization via Markov Decision Processes
by: Folch, Jose Pablo, et al.
Published: (2024)

Fair Resource Allocation in Weakly Coupled Markov Decision Processes
by: Tu, Xiaohui, et al.
Published: (2024)

Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction
by: De Santi, Riccardo, et al.
Published: (2024)

Best-of-Both-Worlds for Heavy-Tailed Markov Decision Processes
by: Chen, Yu, et al.
Published: (2026)

A Markov Decision Process for Variable Selection in Branch & Bound
by: Strang, Paul, et al.
Published: (2025)

Learning Markov Decision Processes under Fully Bandit Feedback
by: Zhuo, Zhengjia, et al.
Published: (2026)

Logarithmic Regret of Exploration in Average Reward Markov Decision Processes
by: Boone, Victor, et al.
Published: (2025)

Rate-Optimal Policy Optimization for Linear Markov Decision Processes
by: Sherman, Uri, et al.
Published: (2023)

Policy Gradient Algorithms with Monte Carlo Tree Learning for Non-Markov Decision Processes
by: Morimura, Tetsuro, et al.
Published: (2022)

Online Markov Decision Processes with Terminal Law Constraints
by: Moreno, Bianca Marin, et al.
Published: (2026)