Research Focus

The Intelligent Information Systems (IIS) group at KIZI (one of its four research groups, overarched by the virtual Knowledge Engineering Group) undertakes research in designing and using intelligent systems and investigating their theoretical grounding. The focal areas of the group currently are:

  • Designing and using logic-based, rule-based and case-based expert system shells and providing them with domain- and task-specific knowledge bases
  • Modelling of uncertainty in information systems (including fuzziness, possibilistic models and information theory)
  • Analyzing the properties of observational calculi applicable on association hypotheses discovered in data using analytical tools
  • Study of relationships and differences between human and computational intelligence
  • Software design for intelligent buildings.

Education and research on Artificial Intelligence has been focal for the Department since several decades (almost since the foundation of its predecessor, Dept. of Scientific and Technical Information in early 1980s). The most important artifact of this early period was the SAK expert system shell, developed under the supervision of J. Ivánek and extensively used both in education and inside deployed intelligent systems. Its particularly strong feature was the possibility to switch between different formal models of uncertainty processing.

A marking moment for the AI research at the Department was the foundation of Laboratory for Intelligent Systems as its ‘research spinoff’ in 1996, under the direction of R. Jiroušek. A large part of AI-focused staff moved their research activities to the lab while keeping their bond to the Department, and new researchers, mainly from the Academy of Science, were hired (including J. Vejnarová). A new focal area then became theoretical research on probabilistic and possibilistic models of uncertainty processing. At the same time, the laboratory continued the practice-oriented stream, with the development of tools such as the WISECON system for intelligent support for selecting a computer product in an on-line catalogue (based on Bayesian networks).

After 2000 the research became more diversified. Theoretical research on uncertain reasoning continued. At the same time, a modern implementation of classical expert system shell combining the rule-based and case-based approach appeared under the name of NEST. Further topics (such as agent-based simulation of economic phenomena, principles of hybrid intelligence or intelligent buildings) have been brought in by PhD students.

The research has/had been supported by several research projects, most notably by the long-term research project (2007-2013) funded by the Ministry of Education under no. MSM 6138439910.