SEMDICE: Improving Off-Policy Reinforcement Learning with Entropy Maximization
Published:Dec 10, 2025 19:50
•1 min read
•ArXiv
Analysis
The article likely introduces a novel reinforcement learning algorithm, SEMDICE, focusing on off-policy learning and entropy maximization. The core contribution seems to be a method for estimating and correcting the stationary distribution to improve performance.
Key Takeaways
Reference
“The research is published on ArXiv.”