Research map / Reinforcement learning / Policy gradient and actor-critic
Neural Trust Region/Proximal Policy Optimization Attains Globally Optimal Policy
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
- Simple Policy Optimization (ICML 2025 · similarity 0.90)
- Mirror Descent Policy Optimization (ICLR 2022 · similarity 0.90)
- Reflective Policy Optimization (ICML 2024 · similarity 0.87)
- PPO in the Fisher-Rao geometry (NeurIPS 2026 · similarity 0.87)
- Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning (ICML 2025 · similarity 0.87)
- Trust Region Reward Optimization and Proximal Inverse Reward Optimization Algorithm (NeurIPS 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.