Research map / Learning theory and algorithms / Submodular and game algorithms
Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form 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
- No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium (NeurIPS 2020 · similarity 0.91)
- Function Approximation for Solving Stackelberg Equilibrium in Large Perfect Information Games (AAAI 2023 · similarity 0.90)
- Fast and Furious Learning in Zero-Sum Games: Vanishing Regret with Non-Vanishing Step Sizes (NeurIPS 2019 · similarity 0.90)
- Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games (NeurIPS 2021 · similarity 0.90)
- No-regret Learning in Harmonic Games: Extrapolation in the Face of Conflicting Interests (NeurIPS 2024 · similarity 0.89)
- Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem (NeurIPS 2024 · similarity 0.89)
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.
