How to increase both autonomy and versatility of a knowledge discovery system is a core problem and a crucial aspect of KDD (Knowledge Discovery and Data Mining). We have
been developing a multi-agent based KDD methodology/system called GLS (Global Learning Scheme) for performing multi-aspect
intelligent data analysis as well as multi-level conceptual abstraction and learning. With multi-level and multi-phase process,
GLS increases versatility and autonomy. This paper presents our recent development on the GLS methodology/system.