Research map / Reinforcement learning / Policy gradient and actor-critic

Mind Your Entropy: From Maximum Entropy to Trajectory Entropy-Constrained RL

ICML 2026 · Reinforcement learning › Policy gradient and actor-critic · approach: Model-based RL with guarantees

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

• Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning (ICLR 2025 · similarity 0.90)
• DIME: Diffusion-Based Maximum Entropy Reinforcement Learning (ICML 2025 · similarity 0.89)
• SCOPE-RL: Stable and Quantitative Control of Policy Entropy in RL Post-Training (NeurIPS 2026 · similarity 0.89)
• When Maximum Entropy Misleads Policy Optimization (ICML 2025 · similarity 0.89)
• Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning (NeurIPS 2024 · similarity 0.89)
• Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow (NeurIPS 2024 · similarity 0.88)