Query Based Learning in Multi-Agent Systems

摘要

This study focuses on query based learning in multi-agent systems which include both data management operations and coordination activities. The study is oriented on agent based and database systems with model driven approach (MDA) which provides arrangement of data within a multi-agent system by letting filter with query based learning which supports the decision mechanism within the system. It uses the similarity measure on maximum entropy approach, which is often to find out interesting and meaningful patterns from databases. At the same time, it may generate a variety of rules, such as classification rules, throughout to learning rules of the query based learning process.