AgentJet: Distributed Swarm Training Framework for Agentic RL
AgentJet is a distributed swarm training framework designed for reinforcement learning with large language model (LLM) agents. It features a decoupled multi-node architecture that enables heterogeneous multi-model RL, mixed-task training, fault-tolerant execution, and live code iteration. The framework demonstrates a 6.25x reduction in actor-update time on AppWorld and supports automated, long-horizon RL studies with minimal human intervention.
Why it matters: AgentJet offers a scalable and flexible solution for training LLM agents in complex, multi-turn environments, potentially accelerating research and development in agentic AI systems.
Full story at: arXiv Multiagent Systems ↗