Stanford Research Team Releases AgentFlow: A Next-Generation Reinforcement Learning Framework for Modular, Tool-Using AI Agents

Stanford University releases the trainable intelligent agent framework AgentFlow, enhancing AI decision-making through a modular design. The framework includes four core modules: planner, executor, validator, and generator, which work together through explicit memory. The planner sets sub-goals and selects tools, the executor calls the tools, the validator checks the continuity of the process, forming a closed-loop intelligent decision-making system.