AI RESEARCH
Cyclical Entropy Eruption: Entropy Dynamics in Agent Reinforcement Learning
arXiv CS.LG
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ArXi:2605.27954v1 Announce Type: new Agentic large language models are increasingly used to solve real-world tasks by reasoning over goals, invoking tools, and interacting with external environments. Reinforcement learning provides a natural framework for improving these behaviors, and recent agent RL methods have achieved strong results across domains. However, the