From Trajectories to Differentiated Skills: Cognitive Differentiation for Self-Improving Agents
[Sztuczna inteligencja] Autorzy: Yewei Zhao, Derong Xu, Wei Chen i 6 więcej
Large language model (LLM) agents tackle complex tasks through reasoning and interaction with external environments. Agent skills provide persistent, transferable capabilities that guide task planning, inform contextual decisions, support tool use, and enable executable procedures. Yet existing skill-evolution methods largely organize knowledge around skill artifacts, overlooking the functional heterogeneity within individual skills and its implications for knowledge maintenance and use. Inspired by cognitive science, we propose Cognitive Differentiation in Skill Evolution (CDSE), which evolves a unified skill through four functionally distinct yet coordinated components: Meta, Experience, Tool, and Script. CDSE extracts evidence-grounded semantic gradients from successful and failed trajectories, consolidates them by functional role, and applies component-specific updates and validatio…
- Kategoria arxiv
- cs.AI
- Kategoria
- Sztuczna inteligencja