Preprint Open access
Principles that Guide, Actions that Inform: Agent Evolution via Knowledge Abstraction
Large language model (LLM) agents have demonstrated strong capabilities in interactive environments, yet their ability to continually evolve from experience remains limited. Although fine-tuning enables adaptation, its dependence on parameter access and high computational costs restrict its flexibility, especially for …