Artificial Intelligence Laboratory

Artificial Intelligence Laboratory performs research in the field of machine learning, data mining, inductive logic programming, qualitative reasoning and artificial intelligence approaches to system control. We study methods for learning from noisy data, both in attribute-based learning for classification and regression and in inductive logic programming, craft new visualization methods in the field of data mining and explorative data analysis, and do research in methods forautomatic discovery of concept hierarchies and constructive induction in machine learning. A notable aspect of much of this research is its application to problems in biomedical informatics, ecological modeling, and mechanical engineering.

Collaborators

• Prof. Ivan Bratko, PhD, Head
• Lecturer Aleksander Sadikov, PhD
• Martin Možina, PhD
• Jure Žabkar, PhD
• Matej Guid, PhD
• as. Tadej Janež
• Aljaž Košmerlj
• Vida Groznik

Selected References

LOGIC PROGRAMMING

• Bratko I. Prolog Programming for Artificial Intelligence, Addison-Wesley, 1986; second edition 1990; third edition Addison-Wesley/Pearson Education 2001. [Amazon]

MACHINE LEARNING AND DATA MINING

• Leban G, Zupan B, Vidmar G, Bratko I. VizRank: Data Visualization Guided by Machine Learning. Data Mining and Knowledge Discovery 13(2): 119-136, 2006.
  
• Demšar J. Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research 7: 1-30, 2006.
  
• Sadikov A, Bratko I, Kononenko I. Bias and pathology in minimax search. Theoretical Computer Science 349(2): 268-281, 2005.
  
• Šuc D, Vladušić D, Bratko I. Qualitatively faithful quantitative prediction. Artificial Intelligence 158(2): 189-214, 2004.
• Zupan B, Bohanec M, Demšar J, Bratko I.Learning by discovering concept hierarchies, Artificial Intelligence Journal 109, 211-242 (1999)
• Michalski RS, Bratko I, Kubat M (eds.) Machine Learning and Data Mining: Methods and Applications, Wiley, 1998. [Amazon]
• Kononenko I, Bratko I. Information based evaluation criterion for classifier's performance. Machine Learning Journal 6: 67-80, 1991.
• Bratko I, Mozetič I, Lavrač N. KARDIO: A Study in Deep and Qualitative Knowledge for Expert Systems, MEM Press, Cambridge, Massachusetts, 1989. [Amazon]

BEHAVIOUR CLONING

• Šuc D, Bratko I. Symbolic and qualitative reconstruction of control skill, Electronic Transactions on Artificial Intelligence 3: 1-22, 1999.

BIOINFORMATICS

• Juvan P, Demsar J, Shaulsky G, Zupan B. GenePath: From Mutations to Genetic Networks and Back. Nucleic Acids Research 33 (Web Server issue): W749-W752, 2005.
  
• Van Driessche N, Demsar J, Booth EO, Hill P, Juvan P, Zupan B, Kuspa A, Shaulsky G. Epistasis analysis with global transcriptional phenotypes. Nature Genetics 37(5): 471-477, 2005.
• Curk T, Demsar J, Xu Q, Leban G, Petrovic U, Bratko I, Shaulsky G, Zupan B. Microarray data mining with visual programming. Bioinformatics 21(3): 396-398, 2005.
• Leban G, Bratko I, Petrovic U, Curk T, Zupan B. VizRank: finding informative data projections in functional genomics by machine learning. Bioinformatics 21(3): 413-414, 2005.
• Zupan B, Demsar J, Bratko I, Juvan P, Halter JA, Kuspa A, Shaulsky G. GenePath: a system for automated construction of genetic networks from mutant data, Bioinformatics 19(3): 383-389, 2003.

Events

• Qualitative Reasoning (with I. Bratko and J. Žabkar as chairs)
• Artificial Intelligence in Medicine
• International Conference of Machine Learning

Partners

• Institute of Oncology, Ljubljana (Tanja Čufer, Simona Borštnar)
• Clinical Center, Ljubljana (Dragica Smrke)