Knowledge management for computational intelligence systems

摘要: Computer systems do not learn from previous experiences unless they are designed for this purpose. Computational intelligence (CIS) inherently capable of dealing with imprecise contexts, creating a new solution in each execution. Therefore, every execution CIS is valuable to be learned. We describe an architecture designing that includes knowledge management (KM) framework, allowing the system its own experiences, and those learned external contexts. This framework makes flexible adaptable so it evolves, guaranteeing high levels reliability when performing dynamic world. KM being incorporated into computational tool software testing at National Institute Systems Test Productivity. paper introduces describing two underlying methodologies uses, i.e. case-based reasoning monitored distribution; also details motivation requirements incorporating CIS.