Dorian Šuc Homepage

Dorian Šuc, Ph.D.
E-mail: dorian.sucXfri.uni-lj.si  (replace X by @)
Web address: http://ai.fri.uni-lj.si/dorian/

Since I left the university, I do research in automated trading, machine learning and intelligent data analysis of financial data for a hedge fund.

I was Assistant Proffesor at Faculty of Computer and Information Science, University of Ljubljana and a member of Artificial Intelligence Laboratory. My research interests (see Publications of Doiran Šuc) include artificial intelligence and in particular machine learning, data mining, and intelligent data analysis. I worked on machine learning in dynamical systems, regression learning, intelligent data analysis, including analysis of financial data, learning monotonicity constraints from numerical data, human skill reconstruction, behavioural cloning and dynamic system control by ML, reinforcement learning, pattern recognition and computer vision, qualitative modeling and combining different types of learning.

See also:

Publications of Dorian Šuc

Here are some selected publications until 2007. See also my page about QUIN and Qualitatively Faithful Numerical Learning, and page about human skill reconstruction, behavioural cloning and dynamic system control by ML.

Book

Šuc, D., Machine Reconstruction of Human Control Strategies, IOS PRess, Amsterdam, The Netherlands, 2003. Based on the dissertation awarded by the 2001 ECCAI Artificial Intelligence Dissertation Award.

Journal Papers

Šuc, D., Vladušič, D., Bratko, I. Qualitatively faithful quantitative prediction. Artificial Intelligence, vol 158, no.2, 2004. pp. 189-214, 2004, ISSN 0004-3702. Preprints. Download at Science Direct

Bratko, I., Šuc, D. Learning qualitative models. AI Magazine. vol 24, no. 4, pp. 107-119, 2004. Link to AI Magazine.

Bratko, I., Šuc, D. Qualitative data mining and its applications. CIT. J. Comput. Inf. Technol., 2003, vol. 11, no. 3, pp. 145-150. ISSN 1330-1136. Link to CIT.

Šuc, D., Bratko, I. Skill modeling through symbolic reconstruction of operator's trajectories. IEEE Transactions on Systems, Man, and Cybernetics, Part A, Syst. humans, 2000, vol. 30, no. 6, pg. 617-624. ISSN 1083-4427. Link to IEEE Transactions at DBLP 

Šuc, D., Bratko, I. Qualitative trees applied to bicycle riding. Electronic Transactions on Artificial Intelligence, 2000, vol. 4, Section B, pp. 125-140. Download at Linköping University Electronic Press.

Šuc, D., Bratko, I. Symbolic and qualitative reconstruction of control skill. Electronic Transactions on Artificial Intelligence, 1999, vol. 3, Section B, pp. 1-22. Download at Linköping University Electronic Press

Book Chapters, Invited lectures

Bratko, I., Šuc, D. Understanding control strategies. In: Della Riccia, G. (ed.), Dubois, D. (ed.), Kruse, R. (ed.), Lenz, H. (ed.). Planning based on decision theory, (CISM courses and lectures, no. 472). Wien; New York: Springer, cop. 2003, pp. 85-98. ISBN 3-211-40756-1.

Bratko, I., Šuc, D. Qualitative data mining and its applications. In: ITI 2003 : proceedings of the 25th International Conference on Information Technology Interfaces, June 16-19, 2003, Cavtat, Croatia. Zagreb: University of Zagreb, SRCE University Computing Centre, 2003, pp. 3-8.

Bratko, I., Šuc, D. Qualitative explanation of controllers. In: Sixteenth International Workshop on Qualitative Reasoning QR 2002, June 10-12, 2002, Sitges - Barcelona - Catalonia - Spain. Sevilla: Edición Digital, 2002, pp. 1-2.

Bratko, I., Šuc, D. Qualitative data mining. In: The new trends in knowledge processing data mining, semantic web and computational science : the sixth SANKEN international symposium, 2003, pp. 10-12.

Selected Published Scientific Conference Contributions

Mele. K., Maver, J., Šuc, D. Image Categorization Using Local Probabilistic Descriptors, Proceedings of the 18th International Conf. on Pattern Recognition, ICPR 2006, (Extended version of the published paper).

Žabkar, J., Vladušič, D., Žabkar, R., Čemas, D., Šuc, D., Bratko, I. Using Qualitative Constraints In Ozone Prediction, Proceedings of the 19th International Workshop on Qualitative Reasoning, 2005.

Šuc, D., Bratko, I. Combining Learning Constraints and Numerical Regression. Proceedings of 19th International Joint Conference on Artificial Intelligence IJCAI-05, 2005.

Šuc, D., Bratko, I., Sammut, Claude. Learning to Fly Simple and Robust. Machine learning : ECML 2004, Proceedings of the 15th European Conf. on Machine Learning, pp. 407-418. Link to electronic edition.

Šuc, D., Vladušič, D., Bratko, I. Qualitatively faithful quantitative prediction. Proceedings of the eighteenth International Joint Conference on Artificial Intelligence, pp. 1052-1057, San Francisco: Morgan Kaufmann Publishers, 2003. Acapulco, August, 2003.

Šuc, D., Bratko, I. Improving numerical prediction with qualitative constraints. Machine learning : ECML 2003, Proceedings of th 14th European Conf. on Machine Learning, (Lecture notes in computer science, Lecture notes in artificial intelligence, vol. 2837), , pp. 385-396. Berlin; Heidelberg; New York: Springer, cop. 2003.

Bratko, I., Šuc, D. Using machine learning to understand operator's skill. Developments in applied artificial intelligence : proceedings, (Lecture notes in computer science, Lecture notes in artificial intelligence, 2358). pp. 812-823. Berlin [etc.]: Springer, cop. 2002.

Šuc, D., Bratko, I. Qualitative reverse engineering. In: Machine learning : proceedings of the 19th International Conference (ICML 2002), University of New South Wales, Sydney, Australia, July 8-12, 2002. San Francisco: Morgan Kaufmann, 2002, pp. 610-617.  Slides in PowerPoint.

Bandelj, A., Bratko, I., Šuc, D. Qualitative simulation with CLP. In Proceedings of the Sixteenth International Workshop on Qualitative Reasoning, (QR2002), Sitges, Spain, 2002, pp. 5-9.

Šuc, D., Bratko, I. Qualitative induction. In: Fifteenth International Workshop on Qualitative Reasoning, May 17-18, 2001, St. Mary's University San Antonio, Texas. Stoughton: The Printing House, 2001, pg. 13-20. Slides in PowerPoint.

Šuc, D. Learning qualitative strategies. In: IC-AI'2001 : proceedings of the International Conference on Artificial Intelligence, Las Vegas, Nevada, USA June 25-28, 2001. [s.l.]: CSREA Press, 2001, vol. 2, pg. 1016-1022.

Šuc, D., Bratko,  I. Induction of qualitative trees. In: 12th European Conference on Machine Learning, Freiburg, Germany, 2001. Machine learning : ECML 2001 : proceedings, (Lecture notes in computer science, Lecture notes in artificial intelligence, 2167). Berlin [etc.]: Springer, 2001, pg. 442-453. Slides in PowerPoint.

Šuc, D., Bratko, I. Qualitative induction for behavioural cloning. Proceedings of Electrotechnical and Computer Science Conference ERK 2001, Slovenia, Slovene section IEEE, 2001, vol. B, pp. 153-156. Slides in PowerPoint (partially in Slovene). The paper received award for the best paper based on Ph.D. thesis. 

Šuc, D., Bratko, I. Qualitative trees applied to bicycle riding. In: Furukawa, K. (ed.). Machine intelligence 17 : special focus on life long learning and discovery in procedural and declarative knowledge. 2000, pp. 81-93.

Šuc, Dorian, Bratko, I. Problem decomposition for behavioural cloning. In: ECML 2000: 11th European Conference on Machine Learning, Machine learning : ECML 2000 : proceedings, (Lecture notes in computer science, Lecture notes in artificial intelligence, 1810). Berlin [etc.]: Springer, 2000, pg. 382-391.

Šuc, D., Bratko, I. Modelling of control skill by qualitative constraints. In: Thirteenth International Workshop on Qualitative Reasoning, Loch Awe, Scotland, 7-9 June 1999. [Aberystwyth: University of Aberystwyth, 1999], pg. 212-220.

Šuc, D., Bratko, I. Skill modeling through symbolic reconstruction of operator's trajectories. In: Automated systems based on human skill : joint design of technology and organisation : preprints of the 6th IFAC Symposium, 1997. Aachen: University of Technology, Department of Informatics in Mechanical Engineering; Ljubljana: J. Stefan Institute, 1997, pp. 35-38. See also Skill moddeling through symbolic reconstruction of operator's trajectorijes, full version, Techical Report

Šuc, D., Bratko, I. Skill reconstruction as induction of LQ controllers with subgoals. In: IJCAI-97 : proceedings of the fiftheenth International joint conference on artificial intelligence, Nagiya, Japan August 23-29, 1997. Volume 2. [S.l.]: International joint conference on artificial intelligence, 1997, pp. 914-920.

Some Papers in Slovene

Šuc, D. Modeliranje veščine vodenja s simboličnim posploševanjem trajektorij vodenja, (zipped file), Master Th., Faculty of Computer and Information Sciences, University of Ljubljana, Slovenia, 1998

Šuc, D. Modeliranje veščine vodenja s simboličnim posploševanjem trajektorij vodenja. In: ZAJC, Baldomir (ed.). Zbornik sedme Elektrotehniške in računalniške konference ERK '98, 24. - 26. september 1998, Portorož, Slovenija. Ljubljana: IEEE Region 8, Slovenska sekcija IEEE, 1998, vol. A, pg. 413-416.

Šuc, D. Kvalitativno modeliranje veščine vodenja. (In Slovene) V: ZAJC, Baldomir (ed.). Zbornik osme Elektrotehniške in računalniške konference ERK '99, 23. - 25. september 1999, Portorož, Slovenija. Ljubljana: IEEE Region 8, Slovenska sekcija IEEE, 1999, vol. A, pg. 325-328.

Šuc, D. Strojno učenje kvalitativnih strategij vodenja. (In Slovene) In: BAVEC, Cene (ed.), GAMS, Matjaž (ed.). Mednarodna multi-konferenca Informacijska družba, Ljubljana, 1999. Informacijska družba IS'99 : zbornik mednarodne multi-konference, 12. do 14. oktobra 1999, Ljubljana, Slovenija : proceedings of the international multi-conference, 12 - 14 October 1999. Ljubljana: Institut Jožef Štefan, 1999, pg. 68-73.

Thesis (Machine Reconstruction of Human Control Strategies)

Šuc, D. Machine reconstruction of human control strategies, Doctoral dissertation, Ljubljana, 2001. VIII, 175 pages, Ph.D.Th.  Slides in PowerPoint. The dissertation is to be published with IOS Press (in October 2003):  Dorian Šuc, Machine reconstruction of human control strategies, IOS Press, series Frontiers in Artificial Intelligence and Applications.

Abstract: Complex dynamic systems are usually controlled by operators who acquired their skill through years of experience. Typically, such a control skill is sub-cognitive and hard to reconstruct through introspection. The operators cannot completely describe their skill, but can demonstrate it. Therefore an attractive approach to the reconstruction of human control skill involves machine learning from operator's execution traces. The goal is to induce a model of the operator's skill, a control strategy
that helps to understand the skill and can be used to control the system.

Behavioural cloning is an approach to such skill reconstruction. In the "original'' approach to behavioural cloning a strategy is induced as a direct mapping from system's states to actions in the form of a decision or regression tree. This thesis develops new ideas to tackle problems that were generally observed with this approach to human skill reconstruction.

One idea is to decompose the learning problem and induce goal-directed strategies that consider learned models of system's dynamics. We introduce a generalized operator's trajectory that can be seen as a continuously changing subgoal. This improves the robustness of the resulting controllers.

Another idea, that is also relevant to the comprehensibility, is to induce qualitative models of human control skill. We show that such qualitative strategies provide an insight into the operator's control skill. On the basis on our experiments, we believe that qualitative strategies can capture important and non-trivial aspects of human control skill. Qualitative strategies open also other new perspectives to the reconstruction of human control skill, such as reconstruction of individual differences in operators's control styles.

These ideas were implemented and evaluated in dynamic domains including container crane, a double pendulum referred to as the acrobot, and bicycle ridding. To induce qualitative control strategies we developed program QUIN for learning qualitative constraint trees from numerical examples.

Keywords: artificial intelligence, machine learning, qualitative modelling, behavioural cloning, skill reconstruction, human control strategies, dynamic systems, system control.

Back to Dorian's main page