Copertina

Sample Complexity for Markov Decision Processes and Stochastic Optimal Control with Static Risk Measures

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chávez, Cristian, Li, Yan
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Optimization and Control
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Risk-averse formulations of Stochastic Optimal Control and Markov Decision Processes
di: Shapiro, Alexander, et al.
Pubblicazione: (2025)

A Bayesian Composite Risk Approach for Stochastic Optimal Control and Markov Decision Processes
di: Ma, Wentao, et al.
Pubblicazione: (2024)

Computational Hardness of Static Distributionally Robust Markov Decision Processes
di: Li, Yan
Pubblicazione: (2025)

On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes
di: Hau, Jia Lin, et al.
Pubblicazione: (2023)

Optimal Sample Complexity for Average Reward Markov Decision Processes
di: Wang, Shengbo, et al.
Pubblicazione: (2023)

Markov Decision Processes with Value-at-Risk Criterion
di: Xia, Li, et al.
Pubblicazione: (2025)

Rectangularity and duality of distributionally robust Markov Decision Processes
di: Li, Yan, et al.
Pubblicazione: (2023)

Achieving Instance-dependent Sample Complexity for Constrained Markov Decision Process
di: Jiang, Jiashuo, et al.
Pubblicazione: (2024)

Robust Markov Decision Processes on Continuous State Spaces
di: Li, Mengmeng, et al.
Pubblicazione: (2026)

Measurized Markov Decision Processes
di: Adelman, Daniel, et al.
Pubblicazione: (2024)

Optimal Sensor and Actuator Selection for Factored Markov Decision Processes: Complexity, Approximability and Algorithms
di: Bhargav, Jayanth, et al.
Pubblicazione: (2024)

Semismooth Newton Methods for Risk-Averse Markov Decision Processes
di: Gargiani, Matilde, et al.
Pubblicazione: (2025)

On the Convergence Rate of MCTS for the Optimal Value Estimation in Markov Decision Processes
di: Chang, Hyeong Soo
Pubblicazione: (2024)

Stability Analysis of An Integrated Multistage Stochastic Programming and Markov Decision Process Problem
di: Yang, Zhiyao, et al.
Pubblicazione: (2025)

Absorbing Markov Decision Processes
di: Dufour, François, et al.
Pubblicazione: (2023)

Risk-Averse Markov Decision Processes: Applications to Electricity Grid and Reservoir Management
di: Khojaste, Arash, et al.
Pubblicazione: (2026)

Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes
di: Lee, Jongmin, et al.
Pubblicazione: (2025)

Tractable Robust Markov Decision Processes
di: Grand-Clément, Julien, et al.
Pubblicazione: (2024)

Mean Field Markov Decision Processes
di: Bäuerle, Nicole
Pubblicazione: (2021)

Stochastic Optimal Control via Local Occupation Measures
di: Holtorf, Flemming, et al.
Pubblicazione: (2022)

Reoptimization Nearly Solves Weakly Coupled Markov Decision Processes
di: Gast, Nicolas, et al.
Pubblicazione: (2022)

Markov Decision Processes with Recursive Risk Measures
di: Bäuerle, Nicole, et al.
Pubblicazione: (2020)

Quantum Markov Decision Processes: Dynamic and Semi-Definite Programs for Optimal Solutions
di: Saldi, Naci, et al.
Pubblicazione: (2024)

Dynamic Capital Requirements for Markov Decision Processes
di: Haskell, William B., et al.
Pubblicazione: (2024)

Learning Risk Preferences in Markov Decision Processes: an Application to the Fourth Down Decision in the National Football League
di: Sandholtz, Nathan, et al.
Pubblicazione: (2023)

Safe Reinforcement Learning for Constrained Markov Decision Processes with Stochastic Stopping Time
di: Mazumdar, Abhijit, et al.
Pubblicazione: (2024)

Peak Value-at-Risk Estimation of Stochastic Processes using Occupation Measures
di: Miller, Jared, et al.
Pubblicazione: (2023)

Convex Approximations of Random Constrained Markov Decision Processes
di: Varagapriya, V, et al.
Pubblicazione: (2025)

Operator Splitting for Convex Constrained Markov Decision Processes
di: Grontas, Panagiotis D., et al.
Pubblicazione: (2024)

Markov Decision Process Design: A Framework for Integrating Strategic and Operational Decisions
di: Brown, Seth, et al.
Pubblicazione: (2023)

Optimal Risk-Sensitive Scheduling Policies for Remote Estimation of Autoregressive Markov Processes
di: Dutta, Manali, et al.
Pubblicazione: (2024)

Risk-sensitive Markov Decision Process and Learning under General Utility Functions
di: Wu, Zhengqi, et al.
Pubblicazione: (2023)

Error Analysis of Sampling Algorithms for Approximating Stochastic Optimal Control
di: Joshi, Anant A., et al.
Pubblicazione: (2025)

Bellman Optimality of Average-Reward Robust Markov Decision Processes with a Constant Gain
di: Wang, Shengbo, et al.
Pubblicazione: (2025)

Cyber Risk Management and Mitigation via Controlled Stochastic SIS Dynamics: An Optimal Control Approach
di: Na, Shize, et al.
Pubblicazione: (2025)

Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds
di: Sattar, Yahya, et al.
Pubblicazione: (2021)

Non-Sequential Decentralized Stochastic Control Revisited: Causality and Static Reducibility
di: Mrani-Zentar, Omar, et al.
Pubblicazione: (2022)

Inexact Policy Iteration Methods for Large-Scale Markov Decision Processes
di: Gargiani, Matilde, et al.
Pubblicazione: (2024)

Contributions on complexity bounds for Deterministic Partially Observed Markov Decision Process
di: Vessaire, Cyrille, et al.
Pubblicazione: (2023)

Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form
di: Kitamura, Toshinori, et al.
Pubblicazione: (2024)