Research map / Reinforcement learning / MDPs and planning
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Deployment Efficient Reward-Free Exploration with Linear Function Approximation (NeurIPS 2025 · similarity 0.91)
- Improved Bounds for Reward-Agnostic and Reward-Free Exploration (ICML 2026 · similarity 0.90)
- Learning Near Optimal Policies with Low Inherent Bellman Error (ICML 2020 · similarity 0.90)
- Reward-Free Exploration for Reinforcement Learning (ICML 2020 · similarity 0.90)
- Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs (ICML 2023 · similarity 0.90)
- A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs (ICML 2025 · similarity 0.87)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.