✨Scaling Agent Learning via Experience Synthesis

📝 Summary:
DreamGym is a unified framework that synthesizes diverse experiences for scalable online reinforcement learning. It distills environment dynamics into a reasoning-based model to reduce reliance on expensive real-world rollouts. DreamGym significantly improves RL training performance and reduces t...

🔹 Publication Date: Published on Nov 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.03773
• PDF: https://arxiv.org/pdf/2511.03773

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✓ https://t.me/DataScienceT

#ReinforcementLearning #MachineLearning #AI #AgentLearning #ExperienceSynthesis

✨AutoEnv: Automated Environments for Measuring Cross-Environment Agent Learning

📝 Summary:
AutoEnv and AutoEnv-36 provide a standardized framework and dataset for measuring cross-environment agent learning. Their evaluations show that fixed learning methods do not scale across diverse environments, highlighting current limitations in agent generalization.

🔹 Publication Date: Published on Nov 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.19304
• PDF: https://arxiv.org/pdf/2511.19304

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For more data science resources:
✓ https://t.me/DataScienceT

#AI #MachineLearning #AgentLearning #Generalization #ReinforcementLearning