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Projects / Programmes source: ARIS

Artificial intelligence and inteligent systems

Periods
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 

Code Science Field
1.02  Natural Sciences  Computer and information sciences 
Keywords
artificial intelligence, machine learning, knowledge discovery, bioinformatics, data visualization, evolutionary computation, qualitative modelling, applications of artificial intelligence
Evaluation (rules)
source: COBISS
Researchers (45)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  20242  PhD Andraž Bežek  Computer science and informatics  Researcher  2009 - 2013  25 
2.  28779  PhD Zoran Bosnić  Computer science and informatics  Researcher  2009 - 2014  214 
3.  24287  PhD Andrej Bratko  Computer science and informatics  Junior researcher  2009  13 
4.  02275  PhD Ivan Bratko  Computer science and informatics  Head  2009 - 2014  745 
5.  36469  PhD Niko Colnerič  Computer science and informatics  Junior researcher  2013 - 2014 
6.  23399  PhD Tomaž Curk  Computer science and informatics  Researcher  2009 - 2014  254 
7.  37515  PhD Andrej Čopar  Computer science and informatics  Junior researcher  2014 
8.  16324  PhD Janez Demšar  Computer science and informatics  Researcher  2009 - 2014  340 
9.  11770  PhD Aleš Dobnikar  Computer science and informatics  Researcher  2009 - 2013  133 
10.  31049  PhD Erik Dovgan  Computer science and informatics  Researcher  2010 - 2014  144 
11.  34403  PhD Miha Drole  Computer science and informatics  Junior researcher  2011 - 2014 
12.  05026  PhD Bogdan Filipič  Computer science and informatics  Researcher  2009 - 2014  483 
13.  08501  PhD Matjaž Gams  Computer science and informatics  Researcher  2009 - 2014  1,703 
14.  29523  PhD Anton Gradišek  Physics  Researcher  2014  450 
15.  33187  PhD Vida Groznik  Computer science and informatics  Junior researcher  2010 - 2014  78 
16.  28365  PhD Matej Guid  Computer science and informatics  Researcher  2009 - 2014  89 
17.  35424  PhD Tomaž Hočevar  Computer science and informatics  Junior researcher  2012 - 2014  30 
18.  30875  PhD Boštjan Kaluža  Computer science and informatics  Beginner researcher  2009 - 2014  146 
19.  04242  PhD Igor Kononenko  Computer science and informatics  Researcher  2009 - 2014  475 
20.  31885  PhD Aljaž Košmerlj  Computer science and informatics  Researcher  2009 - 2014  34 
21.  14565  PhD Matjaž Kukar  Computer science and informatics  Researcher  2009 - 2014  220 
22.  35423  PhD Timotej Lazar  Computer science and informatics  Junior researcher  2012 - 2014  10 
23.  23398  PhD Gregor Leban  Computer science and informatics  Researcher  2009 - 2014  65 
24.  23581  PhD Mitja Luštrek  Computer science and informatics  Researcher  2009 - 2014  480 
25.  23318  PhD Domen Marinčič  Computer science and informatics  Researcher  2009 - 2014  31 
26.  32926  PhD Miha Mlakar  Computer science and informatics  Junior researcher  2010 - 2014  54 
27.  29021  PhD Martin Možina  Computer science and informatics  Researcher  2010 - 2014  77 
28.  25792  PhD Minca Mramor  Human reproduction  Researcher  2009 - 2014  62 
29.  32041  PhD Darko Pevec  Computer science and informatics  Researcher  2009 - 2014  18 
30.  29884  PhD Rok Piltaver  Computer science and informatics  Technical associate  2010 - 2014  80 
31.  20815  PhD Aleksander Pivk  Computer science and informatics  Researcher  2009 - 2014  34 
32.  37516  Matevž Poberžnik  Computer science and informatics  Junior researcher  2014 
33.  32042  PhD Matija Polajnar  Computer science and informatics  Junior researcher  2009 - 2014 
34.  15295  PhD Marko Robnik Šikonja  Computer science and informatics  Researcher  2009 - 2014  430 
35.  20389  PhD Aleksander Sadikov  Computer science and informatics  Researcher  2009 - 2014  195 
36.  33189  Anže Starič  Computer science and informatics  Junior researcher  2010 - 2014 
37.  15656  PhD Tomaž Šef  Computer science and informatics  Researcher  2009 - 2014  394 
38.  31917  PhD Domen Šoberl  Computer science and informatics  Junior researcher  2013 - 2014  42 
39.  29630  PhD Miha Štajdohar  Computer science and informatics  Beginner researcher  2009 - 2014  21 
40.  29486  PhD Erik Štrumbelj  Computer science and informatics  Researcher  2009 - 2014  116 
41.  28519  PhD Lan Umek  Administrative and organisational sciences  Researcher  2009 - 2014  209 
42.  12536  PhD Blaž Zupan  Computer science and informatics  Researcher  2009 - 2014  533 
43.  29020  PhD Jure Žabkar  Computer science and informatics  Researcher  2011 - 2014  133 
44.  30921  PhD Lan Žagar  Computer science and informatics  Researcher  2014  17 
45.  35422  PhD Marinka Žitnik  Computer science and informatics  Junior researcher  2012 - 2014  84 
Organisations (2)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  0106  Jožef Stefan Institute  Ljubljana  5051606000  91,961 
2.  1539  University of Ljubljana, Faculty of Computer and Information Science  Ljubljana  1627023  16,704 
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
The research program Artificial Intelligence and Intelligent Systems contributes to a number of areas of Artificial Intelligence: machine learning and knowledge discovery in data, qualitative modelling, heuristic search, evolutionary computation, and intelligent tutoring systems. Contributions are of various types: theoretical results, methods and techniques for solving open problems in these areas, freely available implementations of developed methods, and applications in chosen application areas. Several methods and techniques are also of general interest to science outside Artificial Intelligence. These include methods for machine learning and knowledge discovery in data which have become very important part of infrastructure for research in other areas of science like biology, genetics, medicine etc. Results of this program that are of interest from this more general point of view include the following: the popular Orange system for machine learning and data analysis that is continuously being upgraded within this program; data fusion techniques from various data sources with matrix factorization; methods for explanation of classifications produced by induced classifiers, Argument-based machine learning (ABML) that enables standard machine learning approaches to take into account existing knowledge in the form of expert-provided arguments about concrete learning examples; ABML knowledge acquisition loop. The work in qualitative modelling enables a non-traditional way of modelling in science and engineering, that is modelling without numbers, but with qualitative relations instead. Often, only such qualitative relations are known in the problem domain. An approach called Padé to learning qualitative models was developed in this program that enables automatic acquisition of qualitative models from data. Concrete important results of this program include: • A method for data fusion with simultaneous matrix tri-factorisation that produced excellent results in genetic applications • Empirical demonstration that explanations based on attribute interactions are correct and intuitive for any model of learning; a new, better measure of success of classification was introduced • Argument-based machine learning (ABML) and a knowledge acquisition procedure “ABML loop” • A new approach to discovery of abstract concepts in robotic domains • Approaches to robot learning from sensory data • Padé, a new method for qualitative learning based on computing qualitative partial derivatives from numerical data; experimental applications of Padé to real problems like: bacterial infections, robot learning, analysis of wind noise in cars • An approach to robot programming with qualitative planning • Analysis of factors that effect chances of pathology in heuristic search when paradoxically more thorough search that requires more work produces worse results • The speeding up of evolutionary algorithm for multi criteria optimisation DEMO by a parallel implementation and use of substitute models of search space • A new approach that automatically finds patterns, sub-goals and stages of search for a given combinatorial problems; this enables a human to deal with otherwise non-tractable search spaces Some scientific results of this program are of foundational character: the introduction of research into the understanding of how the difficulty of problems for humans can be automatically assessed; automatic discovery of abstract concepts from data, that is concepts that have never been explicitly observed in measured data.
Significance for the country
This research program is particularly important for the development of Slovenia because of its application oriented research and transfer of scientific achievements to practice in many application areas. Also, the program ensures the basis for good quality education in artificial intelligence at the university study level, including doctoral study. Many researchers participating in this program carry out applications in collaboration with users in many, very diverse areas of applications like: medicine, bioinformatics, industrial process control, ambient intelligence, robotics, ecology, support for cultural heritage, computer processing of Slovene language. Examples include concrete realised applications of AI methods in the study and discovery of biomarkers in cancer diseases (lung cancer for example), diagnosis of tremors in neurology, diagnosis of heart disorders, intelligent buildings (for example, building management with optimisation with respect to energy consumption and comfort, ensuring good quality living conditions for the elderly), optimisation of manufacturing processes in high quality steel production, control and optimisation of warehouses, systems for recommendation of films, synthesis and analysis of Slovene speech and computer understanding of Slovene text, support to preserving cultural heritage (for example reassembly of large sets of fragments of old paintings found at historical exploration sites). There are continuously appearing new potential application possibilities, such as development of robotic applications in unstructured environments – automated programming of robots in changing environment, demanding intelligent tutoring systems, such as intelligent programming tutor, etc. As an example of surprising diversity of AI applications we here mention in more detail a current application of of machine learning that enables automatic discovery of long term spatial and temporal regularities from data, either measured data or data produced through simulation models. This enables long term validation of numerical models (that otherwise typically suffice for short term predictions only), as well as the discovery of yet unknown laws in processes in nature, such as the movement of water masses in the Adriatic Sea. Currently planned applications, in collaboration with the Piran biological station, include the prediction of emergence and movement of jellyfish which affects the fishing and tourism in the Northern Adriatic Sea.
Most important scientific results Annual report 2009, 2010, 2011, 2012, 2013, final report, complete report on dLib.si
Most important socioeconomically and culturally relevant results Annual report 2009, 2010, 2011, 2012, 2013, final report, complete report on dLib.si
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