Research map / Reinforcement learning / MDPs and planning
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning
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
- Decision-Focused Learning in MDPs: An Occupancy Measure Approach (NeurIPS 2026 · similarity 0.91)
- Learning Markov State Abstractions for Deep Reinforcement Learning (NeurIPS 2021 · similarity 0.88)
- Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model (NeurIPS 2021 · similarity 0.88)
- SPOT: Scalable Policy Optimization with Trees for Markov Decision Processes (NeurIPS 2025 · similarity 0.88)
- Decision-Focused Learning with Directional Gradients (NeurIPS 2024 · similarity 0.88)
- Bridging State and History Representations: Understanding Self-Predictive RL (ICLR 2024 · 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.