Exploiting action impact regularity and exogenous state variables for offline reinforcement learning

DOI10.1613/JAIR.1.14580MaRDI QIDQ6488780

Martha White, James R. Wright, Vincent S. Liu

Publication date: 23 October 2023

Published in: The Journal of Artificial Intelligence Research (JAIR) (Search for Journal in Brave)

zbMATH Keywords

reinforcement learningbatch reinforcement learningoffline reinforcement learningreal-world reinforcement learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• Title not available (Why is that?)
• Near-optimal reinforcement learning in polynomial time
• 10.1162/153244303765208377
• Using Stochastic Approximation Methods to Compute Optimal Base-Stock Levels in Inventory Control Problems
• A Knapsack Secretary Problem with Applications
• The Secretary Problem and Its Extensions: A Review
• Bandit Algorithms
• Learning Near-Optimal Policies with Bellman-Residual Minimization Based Fitted Policy Iteration and a Single Sample Path
• Performance Bounds in $L_p$‐norm for Approximate Value Iteration

This page was built for publication: Exploiting action impact regularity and exogenous state variables for offline reinforcement learning

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6488780)