Learning Efficiently Function Approximation for Contextual MDP
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Abstract (arXiv)
We study learning contextual MDPs using a function approximation for both the rewards and the dynamics. We consider both the case that the dynamics dependent or independent of the context. For both models we derive polynomial sample and time complexity (assuming an efficient ERM oracle). Our methodology gives a general reduction from learning contextual MDP to supervised learning.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 4 of its 21 references that are in the map. First posted on arXiv 2 Mar 2022.
Builds on
4 of 21 references.
References · 4
- 2015Contextual Markov Decision Processescited by 213
- 2020Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits under Realizabilitycited by 114
- 2016Reinforcement Learning in Rich-Observation MDPs using Spectral Methodscited by 13
- 2016PAC Reinforcement Learning with Rich Observationscited by 4
Built on by
Citing papers per year: 2022: 3; 2023: 2; 2024: 1; 2025: 2; 2026: 2.
10 papers.
- 2022Optimism in Face of a Context: Regret Guarantees for Stochastic Contextual MDPcited by 11
- 2022Eluder-based Regret for Stochastic Contextual MDPscited by 9
- 2023Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximationcited by 9
- 2024Sample Complexity Characterization for Linear Contextual MDPscited by 4
- 2022Provably Efficient Lifelong Reinforcement Learning with Linear Function Approximationcited by 2
- 2023Scaling Distributed Multi-task Reinforcement Learning with Experience Sharingcited by 1
- 2025Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contextscited by 0
- 2025Learning Personalized Ad Impact via Contextual Reinforcement Learning under Delayed Rewardscited by 0
- 2026Interaction-Grounded Learning for Contextual Markov Decision Processes with Personalized Feedbackcited by 0
- 2026Near-Optimal Regret for Policy Optimization in Contextual MDPs with General Offline Function Approximationcited by 0
- 2026Near-Optimal Regret for Policy Optimization in Contextual MDPs with General Offline Function Approximation14 Feb 2026
- 2026Interaction-Grounded Learning for Contextual Markov Decision Processes with Personalized Feedback9 Feb 2026
- 2025Learning Personalized Ad Impact via Contextual Reinforcement Learning under Delayed Rewards22 Oct 2025
- 2025Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contexts10 Jul 2025
- 2024Sample Complexity Characterization for Linear Contextual MDPs5 Feb 2024
- 2023Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing11 Jul 2023
- 2023Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation2 Mar 2023
- 2022Eluder-based Regret for Stochastic Contextual MDPs27 Nov 2022
- 2022Optimism in Face of a Context: Regret Guarantees for Stochastic Contextual MDP22 Jul 2022
- 2022Provably Efficient Lifelong Reinforcement Learning with Linear Function Approximation1 Jun 2022