NetIQ: A Tri-Modular Dynamic Evaluation Framework for Intelligent Agent Networks

This paper proposes NetIQ, a hierarchical evaluation framework for intelligent agent networks that integrates Network Knowledge Linking (NKL), Group Collaboration Synergy (GCS), and Autonomous Cognitive Capability (ACC) into a dynamically quantifiable system via differential coupling equations. Grounded in information theory, game theory, and cognitive science, NetIQ implements a nine-tier intelligence classification with adaptive thresholds. Multimodal attack simulations demonstrate rapid recovery and key innovations: better OODA cycle efficiency gain through dynamic feedback; higher root-cause diagnosis accuracy via modular causal tracing; and environmentadaptive thresholds for heterogeneous scenarios.