The research in the domain of autonomous intelligent agent is the foreground of the introduction of artificial intelligence solution in all areas of economy. The intelligent autonomous systems combine the usage of pattern recognition, reasoning, decision making, conceptual modeling techniques and methods. The important part of intelligent agent implementation is to find the conceptualization which is suitable to the current problematic situation. Despite all progress around autonomous intelligent agents, humans are much more flexible and creative in making the right conceptualizations.
The paper is devoted to the research and development of methods and tools for identifying problematic situations on the basis of ontologies using the mechanisms of logical inference that are used in intellectual decision support systems for software testing problems.
The important problem of software testing using ontological modeling for timely detection of errors and improvement of quality of the developed software is considered.
The article contains information technology for identification of problematic situations and their states in complex technical systems, which is based on a method that is based on the information model identification process and modified clustering algorithms such situations FOREL and K-MEANS.