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Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses

Microsoft Researchen

1mes

Antigüedad

Publicado
Recolectado

Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research .

Extracto de la fuente

At a glance Harnessed Agentic RL: Microsoft Research Asia introduces a training paradigm in which the same agent harness used in deployment participates directly in reinforcement learning, removing the need to reimplement the agent inside the training framework. Lightweight by design: Agent Lightning v1.0 delivers a complete agent RL control plane in roughly 3,500 lines of code. Native Kubernetes support: agents run as standard Kubernetes jobs on self-managed clusters, cloud Kubernetes, or…

overfeed.news indexa y enlaza. Publicamos un extracto breve; el artículo completo sigue en Microsoft Research.

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Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL…