Existing Multiagent systems are typically built around predefined agent roles and static workflow. They have limited ability to create new specialist agents at runtime, evaluate their effectiveness and adapt their workflow based on task requirements. This work proposes a self evolving multistage framework that dynamically synthesis agents, constructs adaptive workflows, evaluates agent performance and refinance future executions through accumulated experience
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