SEMDICE: Improving Off-Policy Reinforcement Learning with Entropy Maximization

Research#Agent🔬 Research|Analyzed: Jan 10, 2026 12:13•
Published: Dec 10, 2025 19:50
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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.
Reference / Citation
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ArXivDec 10, 2025 19:50
* Cited for critical analysis under Article 32.
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Source: ArXiv