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General Information \ Department of A.I. \ Foundations of Artificial Intelligence Site Map  

Foundations of
Artificial Intelligence

Statistical Analysis
and Modelling

Game and Decision
Theory

Linguistic
Engineering

 

Department of
Artificial Intelligence

Department of
Theoretical
Foundations of
Computer Science

 

General Information

 
FOUNDATIONS
OF ARTIFICIAL INTELLIGENCE

Group Members
Mieczysław Kłopotek, Ph.D., Professor, Head of the Group
Piotr Borkowski, M.Sc.
Szymon Chojnacki, M.Sc.
Krzysztof Ciesielski, Ph.D.
Dariusz Czerski, Ph.D.
Roman ¦winiarski, Ph.D.,Professor
Marcin Sydow, Ph.D.
Krzysztof Trojanowski, Ph.D., Associate Professor
Sławomir Wierzchoń, Ph.D., Professor

Foreign Associates

Zbigniew Michalewicz, Ph.D., Professor,
University of Adelaide
Zbigniew Ra¶, Ph.D., Associate Professor,
University of North Carolina

Research Areas
The research group is active in the field of intelligent systems in the following research areas:
knowledge discovery engineering
  • internet search engines
  • knowledge discovery from data, text and hypertext
meta-heuristics in optimization
  • optimization in dynamic environments
  • nature-inspired optimization methods.

The research group is working on massively parallel search engine to work with the Polish Internet resources in a novel way. Our specialty is to systematize online resources and making the systematics perceivable to the user. Systematization means the automatic distribution of online resources for thematic groups, highlighting thematic channels in websites, labeling and categorizing documents and their groups. >From the user point of view, this translates into not only a more precise document identification. Systematization also gives the ability to search the context of both individual documents and groups, such as channels or services and to diversify the search engine response.
Diversification means the variation in response, so that the user see not only the best papers, but also the variety and thematic ambiguity, such as for example in the classic question of "game" which may refer to playing or be a term understandable for hunters only. Taking into account the context is important when looking for a document that is comprehensible only in the environment of other documents in a particular thematic channel. For example, asking a search engine - fairly common in autumn and spring seasons - to inquire about the tires we would expect the response of links to sites that are manufacturers tires or tire shops and not e.g. of a hard work that makes us tired. Taking into account the context will allow the search engine return links to such documents, containing in its content of the word "tire" in which there is no word "car".
Thus understood systematization will be a useful tool for many groups of users. Scientists and entrepreneurs will be able to \look for potential partners or competitors in the market. On the other hand, systematizing helps them to identify interesting research areas or gaps in the market that can be exploited.
A promising direction of research is the use of search engine technology and tools acquiring knowledge from data, text and hypertext to analyze social networks.
An integral part of the outlined research is optimization. The research group focuses on the so-called meta-heuristic methods and algorithms based on evolutionary, immunological, or swarm intelligence methods. The main advantage of methods developed ourselves in the diversification of obtained solutions, which can not be overestimated especially in the case of a large dynamic environment optimization system. Besides search engine technology they can find broad application areas like optimization of chemical reactions, in the control of production processes or in the simulation of social processes.
Both in the case studies of social networks and wide use of dynamic environments we exploit simulation tools constructed by the team (based on our theoretical studies) for the generation of synthetic data similar to real world ones.
We also conduct research in the classic areas of knowledge acquisition from data, but with in-depth analysis of the acquisition of so-called active classifiers, i.e. based on the distinguishing characteristics of these objects, which can be controlled and which can’t.
In these and other areas of intelligent systems cooperate with Polish search engine industry wyszukiwarkowym, foreign companies involved in the modeling market, as well as with Polish universities as the University of Cardinal Stefan Wyszynski, the Polish-Japanese Institute of Information Technology, University of Nature and the Humanities, University of Gdansk, Wroclaw University of Technology and abroad as the name of the Max Planck Institute of Computer Science (EU), University of North Carolina at Charlotte (USA) San Diego State University (USA) and University of Adelaide (Australia).



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