Research map / Reinforcement learning / MDPs and planning
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| layer-by-layer exploration with generalized G-optimal design plus exploration-preserving policy discretization | reward-free RL with linear MDP · linear MDP | deployment complexity | Helped |
Closest papers by meaning
- Deployment Efficient Reward-Free Exploration with Linear Function Approximation (NeurIPS 2025 · similarity 0.95)
- Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality (ICLR 2022 · similarity 0.94)
- Reward-Free Exploration for Reinforcement Learning (ICML 2020 · similarity 0.91)
- On Reward-Free Reinforcement Learning with Linear Function Approximation (NeurIPS 2020 · similarity 0.90)
- Scalable Online Exploration via Coverability (ICML 2024 · similarity 0.90)
- Reward-Free Kernel-Based Reinforcement Learning (ICML 2024 · similarity 0.89)
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