Finite-Sample Theory for Fitted Q-Iteration When Actions Are Functions

arXiv:2609.36390 · stat.ME, cs.LG, math.ST, stat.ML, stat.TH · Submitted 2026-09-28 · Read on arXiv

stat.ME, cs.LG, math.ST, stat.ML, stat.TH

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/gefeilin/Functional-Fitted-Q-Learning

Terminology

• Accuracy — 43× in this paper · explained in 1 episode
• Reinforcement Learning — 17× in this paper · explained in 4 episodes
• Verification — 17× in this paper · explained in 2 episodes
• Calibration — 13× in this paper · explained in 7 episodes
• Regularization — 6× in this paper · explained in 3 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• Regret — 5× in this paper · explained in 3 episodes
• Action Space — 4× in this paper · explained in 1 episode
• Approximation Bound — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Hilbert Space — 3× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 3× in this paper
• International Conference on Machine Learning — 3× in this paper
• Adam — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Sample Complexity — 2× in this paper · explained in 15 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reproducing Kernel Hilbert Space (RKHS) — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• OpenAI Gym
• Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
• Precision Physical Activity Prescription via Reinforcement Learning for Functional Actions
• Fixing an error in Caponnetto and de Vito (2007)
• Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage

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