Copertina

Statistical Inference of the Value Function for Reinforcement Learning in Infinite Horizon Settings

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Shi, C., Zhang, S., Lu, W., Song, R.
Natura:	Preprint
Pubblicazione:	2020
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Infinite-Horizon Reinforcement Learning with Multinomial Logistic Function Approximation
di: Park, Jaehyun, et al.
Pubblicazione: (2024)

Statistical Inference in Reinforcement Learning: A Selective Survey
di: Shi, Chengchun
Pubblicazione: (2025)

Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning
di: Moulin, Antoine, et al.
Pubblicazione: (2025)

Provably Efficient Infinite-Horizon Average-Reward Reinforcement Learning with Linear Function Approximation
di: Chae, Woojin, et al.
Pubblicazione: (2024)

Policy Zooming: Adaptive Discretization-based Infinite-Horizon Average-Reward Reinforcement Learning
di: Kar, Avik, et al.
Pubblicazione: (2024)

Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs via Approximation by Discounted-Reward MDPs
di: Hong, Kihyuk, et al.
Pubblicazione: (2024)

Deep Reinforcement Learning for Infinite Horizon Mean Field Problems in Continuous Spaces
di: Angiuli, Andrea, et al.
Pubblicazione: (2023)

Nonparametric Additive Value Functions: Interpretable Reinforcement Learning with an Application to Surgical Recovery
di: Emedom-Nnamdi, Patrick, et al.
Pubblicazione: (2023)

Statistical Inference for Temporal Difference Learning with Linear Function Approximation
di: Wu, Weichen, et al.
Pubblicazione: (2024)

Infinite-Horizon Reach-Avoid Zero-Sum Games via Deep Reinforcement Learning
di: Li, Jingqi, et al.
Pubblicazione: (2022)

Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span
di: Chae, Woojin, et al.
Pubblicazione: (2024)

Conformal Prediction Beyond the Horizon: Distribution-Free Inference for Policy Evaluation
di: Gan, Feichen, et al.
Pubblicazione: (2025)

Exchange Policy Optimization Algorithm for Semi-Infinite Safe Reinforcement Learning
di: Zhang, Jiaming, et al.
Pubblicazione: (2025)

Horizon Generalization in Reinforcement Learning
di: Myers, Vivek, et al.
Pubblicazione: (2025)

Active Value Querying to Minimize Additive Error in Subadditive Set Function Learning
di: Černý, Martin, et al.
Pubblicazione: (2026)

Reinforcement Learning from Human Feedback: A Statistical Perspective
di: Liu, Pangpang, et al.
Pubblicazione: (2026)

UDQL: Bridging The Gap between MSE Loss and The Optimal Value Function in Offline Reinforcement Learning
di: Zhang, Yu, et al.
Pubblicazione: (2024)

On the Importance of Multistability for Horizon Generalization in Reinforcement Learning
di: Bakija, Asad, et al.
Pubblicazione: (2026)

Inverse Reinforcement Learning with Multiple Planning Horizons
di: Yao, Jiayu, et al.
Pubblicazione: (2024)

Stochastic Decision Horizons for Constrained Reinforcement Learning
di: Milosevic, Nikola, et al.
Pubblicazione: (2026)

Issues with Value-Based Multi-objective Reinforcement Learning: Value Function Interference and Overestimation Sensitivity
di: Vamplew, Peter, et al.
Pubblicazione: (2024)

Factored Value Functions for Graph-Based Multi-Agent Reinforcement Learning
di: Rashwan, Ahmed, et al.
Pubblicazione: (2026)

Fixing Incomplete Value Function Decomposition for Multi-Agent Reinforcement Learning
di: Baisero, Andrea, et al.
Pubblicazione: (2025)

Statistical Learning from Attribution Sets
di: Applebaum, Lorne, et al.
Pubblicazione: (2026)

Statistical Inference for Fuzzy Clustering
di: Wu, Qiuyi, et al.
Pubblicazione: (2026)

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

Learning Set Functions with Implicit Differentiation
di: Özcan, Gözde, et al.
Pubblicazione: (2024)

Online Learning with Set-Valued Feedback
di: Raman, Vinod, et al.
Pubblicazione: (2023)

What Makes Value Learning Efficient in Residual Reinforcement Learning?
di: Ma, Guozheng, et al.
Pubblicazione: (2026)

On the Effective Horizon of Inverse Reinforcement Learning
di: Xu, Yiqing, et al.
Pubblicazione: (2023)

Horizon Reduction as Information Loss in Offline Reinforcement Learning
di: Nidadala, Uday Kumar, et al.
Pubblicazione: (2025)

Learning U-Statistics with Active Inference
di: Wang, Xiaoning, et al.
Pubblicazione: (2026)

A Physics-Informed Learning Framework to Solve the Infinite-Horizon Optimal Control Problem
di: Fotiadis, Filippos, et al.
Pubblicazione: (2025)

VIPO: Value Function Inconsistency Penalized Offline Reinforcement Learning
di: Chen, Xuyang, et al.
Pubblicazione: (2025)

Demystifying Reinforcement Learning for Long-Horizon Tool-Using Agents: A Comprehensive Recipe
di: Wu, Xixi, et al.
Pubblicazione: (2026)

MARPLE: A Benchmark for Long-Horizon Inference
di: Jin, Emily, et al.
Pubblicazione: (2024)

Set-Valued Policy Learning
di: Fuentes-Vicente, Laura, et al.
Pubblicazione: (2026)

The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes
di: Santos, Pedro P., et al.
Pubblicazione: (2024)

Reinforcement Learning with Random Time Horizons
di: Borrell, Enric Ribera, et al.
Pubblicazione: (2025)

Investigating Lagrangian Neural Networks for Infinite Horizon Planning in Quadrupedal Locomotion
di: Kotecha, Prakrut, et al.
Pubblicazione: (2025)