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This article introduces a new framework for agent evolution based on procedural memory. The focus is on how agents can learn and improve from their experiences. The title suggests a system that not only stores memories but also actively refines them, implying a dynamic and adaptive learning process. The source, ArXiv, indicates this is a research paper, likely detailing the technical aspects of the framework.
Reference