Research map / Reinforcement learning / MDPs and planning
Bilevel Optimization over Saddle Points of Zero-Sum Markov Games
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
- Contextual Bilevel Reinforcement Learning for Incentive Alignment (NeurIPS 2024 · similarity 0.91)
- Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem (NeurIPS 2024 · similarity 0.89)
- PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback (ICLR 2024 · similarity 0.89)
- Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence beyond the Minty Property (AAAI 2024 · similarity 0.88)
- On the Sample Complexity Bounds of Bilevel Reinforcement Learning (NeurIPS 2025 · similarity 0.88)
- Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator (NeurIPS 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.