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Projects / Programmes source: ARIS

Artificial intelligence and inteligent systems

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Periods
January 1, 2004 - December 31, 2008
Research activity

Code Science Field Subfield
2.07.00  Engineering sciences and technologies  Computer science and informatics   
2.06.00  Engineering sciences and technologies  Systems and cybernetics   
1.07.00  Natural sciences and mathematics  Computer intensive methods and applications   
2.10.00  Engineering sciences and technologies  Manufacturing technologies and systems   

Code Science Field
P170  Natural sciences and mathematics  Computer science, numerical analysis, systems, control 
Keywords
artificial intelligence, machine learning, knowledge discovery, bioinformatics, data visualization, evolutionary computation, qualitative modelling, applications of artificial intelligence
Evaluation (rules)
source: COBISS
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Researchers (36)
no. Code Name and surname Research area Role Period No. of publications
1.  21306  PhD Matjaž Bevk  Computer science and informatics  Researcher  2004 - 2008  19 
2.  20242  PhD Andraž Bežek  Computer science and informatics  Researcher  2004 - 2008  25 
3.  15745  Robert Blatnik    Technical associate  2004 - 2008  75 
4.  28779  PhD Zoran Bosnić  Computer science and informatics  Researcher  2008  211 
5.  24287  PhD Andrej Bratko  Computer science and informatics  Junior researcher  2006 - 2008  13 
6.  02275  PhD Ivan Bratko  Computer science and informatics  Head  2004 - 2008  740 
7.  23399  PhD Tomaž Curk  Computer science and informatics  Researcher  2004 - 2008  246 
8.  02590  PhD France Dacar  Mathematics  Researcher  2005 - 2008  42 
9.  16324  PhD Janez Demšar  Computer science and informatics  Researcher  2004 - 2008  340 
10.  11770  PhD Aleš Dobnikar  Computer science and informatics  Researcher  2004 - 2008  131 
11.  11973  PhD Matija Drobnič  Computer science and informatics  Researcher  2004 - 2008  63 
12.  05026  PhD Bogdan Filipič  Computer science and informatics  Researcher  2004 - 2008  470 
13.  08501  PhD Matjaž Gams  Computer science and informatics  Researcher  2004 - 2008  1,649 
14.  28365  PhD Matej Guid  Computer science and informatics  Junior researcher  2007 - 2008  84 
15.  20225  PhD Aleks Jakulin  Computer science and informatics  Researcher  2004  38 
16.  21352  PhD Peter Juvan  Human reproduction  Researcher  2004 - 2007  163 
17.  04242  PhD Igor Kononenko  Computer science and informatics  Researcher  2004 - 2008  475 
18.  10467  PhD Matevž Kovačič  Medical sciences  Researcher  2004 - 2006  14 
19.  11562  PhD Viljem Križman  Computer science and informatics  Researcher  2004 - 2006  30 
20.  14565  PhD Matjaž Kukar  Computer science and informatics  Researcher  2004 - 2008  215 
21.  02571  Mitja Lasič  Computer science and informatics  Technical associate  2004 - 2008  24 
22.  13207  PhD Momir Lazović  Mechanical design  Researcher  2004  72 
23.  23398  PhD Gregor Leban  Computer science and informatics  Researcher  2004 - 2008  60 
24.  23581  PhD Mitja Luštrek  Computer science and informatics  Researcher  2004 - 2008  461 
25.  23318  PhD Domen Marinčič  Computer science and informatics  Junior researcher  2005 - 2008  31 
26.  25792  PhD Minca Mramor  Human reproduction  Junior researcher  2006 - 2008  58 
27.  20815  PhD Aleksander Pivk  Computer science and informatics  Researcher  2004 - 2008  34 
28.  15295  PhD Marko Robnik Šikonja  Computer science and informatics  Researcher  2004 - 2008  394 
29.  20389  PhD Aleksander Sadikov  Computer science and informatics  Researcher  2004 - 2008  183 
30.  23401  PhD Luka Šajn  Computer science and informatics  Researcher  2004 - 2008  105 
31.  15656  PhD Tomaž Šef  Computer science and informatics  Researcher  2004 - 2008  390 
32.  02832  PhD Marjan Špegel  Computer science and informatics  Researcher  2004 - 2008  79 
33.  15754  PhD Dorian Šuc  Computer science and informatics  Researcher  2004 - 2008  43 
34.  28519  PhD Lan Umek  Administrative and organisational sciences  Junior researcher  2007 - 2008  195 
35.  21305  PhD Daniel Vladušič  Computer science and informatics  Researcher  2004 - 2008  47 
36.  12536  PhD Blaž Zupan  Computer science and informatics  Researcher  2004 - 2008  524 
Organisations (2)
no. Code Research organisation City Registration number No. of publications
1.  0106  Jožef Stefan Institute  Ljubljana  5051606000  87,195 
2.  1539  University of Ljubljana, Faculty of Computer and Information Science  Ljubljana  1627023  14,814 
Abstract
The members of the group carry out research in the following fields: • machine learning and knowledge discovery; • genetic algorithms and search algorithms; • constraint programming and combinatorial optimization; • qualitative reasoning methods; • machine learning in biomedical informatics; • agent technologies and semantic web. The research is constantly motivated with practical uses and concrete applications. Selected scientific achievements for the year 2005: • Analysis and reconstruction of genetic networks on the basis of microarray profiles, published also in van Driessche, Demšar, Juvan, Zupan, et al. Epistasis analysis with global transcriptional phenotypes. Nature Genetics, May 2005, impact factor 24.69. • Intelligent visualization of data using machine learning, published in (Leban et al., VizRank: finding informative data projections in functional genomics by machine learning; and in Curk et al., Microarray data mining with visual programming) Bioinformatics, #1 ranking journal in computer science. • Argument-based machine learning: a new approach to machine learning where the expert in the domain being learned can comment the learning examples with his or her arguments (explaining selected details in the learning examples). • Genetic algorithm for the analysis of complex biological systems with EPR spectroscopy (two papers in leading journals), and a genetic algorithm for steel production optimization introduced into use in steel mills Acroni Jesenice (Slovenia) and Ruuki Steel (Finland). • Machine learning of qualitative models from numerical data with our original method Q2 with application in ecological domains (predicting ozone concentration and Savinja river flooding). • System for automatic discovery of abnormalities in scintigraphic images of skeletons; in collaboration with the Clinic for Nuclear Medicine in Ljubljana. • Contributions to technology of Slovenian language: automatic accentuation of Slovenian words, use of ontologies for interpretation, continuing development of system “GOVOREC”. International awards in 2005: • ECCAI award for the best doctoral dissertation in artificial intelligence in Europe in 2005: A. Jakulin, Machine Learning Based on Attribute Interactions. • First award in NIST (USA) competition of e-mail spam filters (A. Bratko and B. Filipič). Fields of applicative research: • medicine; • bioinformatics and functional genomics; • system identification and management; • environmental issues; • engineering applications (textile industry, mechanical engineering); • internet applications (e-mail spam filtering, intelligent browsers); • marketing and economy.
Significance for science
This research programme made contributions to several problems of current interest in the area of Artificial Intelligence. These contributions are important because of the impact and high applicability of this area of Computer Science. In our assessment, the results of this programme will significantly contribute to the development of the addressed topics of AI, development of practical programming tools, and confirmation of the applicability in practice of the scientific innovations. A number of results of this program are important for the development of machine learning in AI, both in terms of new approaches and algorithms (e.g. argument-based machine learning, qualitative learning, Q2 learning, methods of intelligent information visualisation), and powerful application tools (such as Orange system). Some of the application-oriented research of this program also contributes to other sciences, concretely for example to genetic research. Methods developed in this programme enable automatic construction of new scientific theories from experimental data (for example from observations from genetic experiments). Some scientific results of this programme are also significant for the progress in the theory of search methods in AI. This includes the analysis of “pathology” in search algorithms, as well as the paradox discovered in this programme, that in “real-time search” pessimistic heuristics are more successful, in contrast to the previously known benefits of optimistic heuristics in search algorithms in general. The question of what intelligence is and how it comes about is a key and yet unanswered question of science and philosophy. Some results of this programme also contribute to this question, and are, among others, relevant to the philosophical question of (im)possibility of automation of research, in particular of automatically constructing new scientific hypotheses. Our results indicate a positive answer to this question. The development of new methods in this programme is not only important for the progress in computer science. Approaches of AI, like machine learning, knowledge discovery in data, representation and use of domain knowledge, qualitative modelling and design of intelligent systems, are becoming, or have become, key part of the infrastructure of other sciences. Examples of recent such advances are in functional genomics (application of heuristic search methods) and modern approaches to clinical diagnosis (prediction models based on gene expression).
Significance for the country
We strive to apply the findings of our research in practice as much as possible. Some examples in recent years: quality control in light construction sandwich panel production at Trimo, predicting the appearance of clothing on the basis of physical and mechanical properties of textiles at Mura (in collaboration with Textile Department at University of Maribor), the system for speech synthesis for Slovenian language GOVOREC, predicting the danger of flooding by Slovenian rivers. System GOVOREC enables computer speech synthesis of Slovenian texts. Most likelz, its biggest contribution is helping handicapped people in their everyday life. With the use of qualitative modelling we constructed a predictive model for the level of Savinja river. Since Savinja is a torrentous river its level can rapidly change. Our model can serve as an early warning system against flooding. Apart from scientific work, the members of the group teach various courses (mostly AI and programming) at the University of Ljubljana and to a lesser extent at the University of Maribor, University of Nova Gorica and the Jožef Stefan International Postgraduate School. The textbook Prolog Programming for Artificial Intelligence by Ivan Bratko, the head of the group, has been translated into a number of languages, and is the most widely used textbook on prolog programming language in the world. We are continuously developing an open-source machine learning suite Orange (www.ailab.si/orange), among the largest of its kind in the world. The suite boasts a graphical user interface that enables visual programming which in turn enables even non-programmers (like experts from other fields, e.g. biologists or geneticists) to create complex procedures from Orange’s numerous basic building blocks. In collaboration with biologists and geneticists we developed Orange modules for processing and analysis of bioinformatics and functional genomics data. The most high-profile result of this work is the finding that it is possible to reason about relations between genes on the basis of transcriptional profiles of mutants (Van Driessche et al., Epistasis analysis with global transcriptional phenotypes, Nature Genetics 37(5): 471-477, 2005). In the last five years the members of the group have earned two prestigious awards for the best European doctoral dissertation in artificial intelligence awarded by ECCAI, the European Coordinating Committee for Artificial Intelligence.
Most important scientific results Final report, complete report on dLib.si
Most important socioeconomically and culturally relevant results Final report, complete report on dLib.si
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