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Artificial Intelligence
Laboratory
Head: akad. prof. dr. Ivan Bratko
Team
Prof. dr. Ivan Bratko
Tadej Janež
dr. Aleksander Sadikov
Vida Groznik
dr. Jure Žabkar
Aljaž Košmerlj
Artificial Intelligence Laboratory
dr. Martin Možina
dr. Matej Guid
Current projects/research
• Cognitive Robotics
• Machine Learning for Building Intelligent
Tutoring Systems
• Molecular and Other Prognosticators of Lung
Cancer and Mesothelioma
• GuruCue: Recommender Systems
• 3R Tim: Optimization of Warehouse Logistics
Artificial Intelligence Laboratory
Autonomous discovery of concepts
•
Košmerlj, A., Bratko, I., Žabkar, J.: Embodied concept discovery through qualitative action models.
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS)
• Leban, G., Žabkar, J., Bratko, I.: An Experiment in Robot Discovery with ILP.
In: Proceedings of the eighteenth International Conference on Inductive Logic Programming (ILP)
Artificial Intelligence Laboratory
Learning in a complex environment
• Janež, T., Žabkar, J., Možina, M., Bratko, I.: It may be faster to learn in a more complex environment.
Sent to: Journal of Autonomous Agents and Multi-Agent Systems
Artificial Intelligence Laboratory
Machine Learning for Building Intelligent Tutoring Systems
• Partner: Department of Neurology,
University Medical Centre, Ljubljana
• ITS for:
– symbolic problem-solving domains (chess, tremor diagnosis)
– motor skill domains (walking in patients – multiple sclerosis)
•
•
Groznik, V., Guid, M., Sadikov, A., Možina, M., Georgiev, D., Kragelj, V., Ribarič, S., Pirtošek, Z., Bratko, I..
Elicitation of neurological knowledge with ABML.
Invited to: Artificial Intelligence in Medicine.
Sadikov, A., Možina, M., Guid, M., Krivec, J., Bratko, I. Automated chess tutor.
Lect. notes comput. sci., str. 13-25, 2007
Artificial Intelligence Laboratory
Molecular and Other Prognosticators of Lung Cancer and Mesothelioma
• Partner: University Clinic of Respiratory and Allergic
Diseases, Golnik
• Data analysis
• Help with experimental design setup
• Designing a tool for survival estimation based on individual
patient’s characteristics
(clinico-pathological data and new markers)
•
•
•
Borštnar, S., Sadikov, A., Možina, B., Čufer, T. High levels of uPA and PAI-1 predict a good response to
anthracyclines. Breast cancer res. treat., 2010, vol. 121, no. 3, pgs. 615-624
Ovčariček, T., Triller, N., Sadikov, A., Čufer, T. Prognostic value of C-reactive protein and other classical
factors in patients with advanced non-small cell lung carcinoma treated in routine clinical practice.
Zdrav Vestn, 2010, vol. 79, no. 10, str. 669-676
Golouh, R., Čufer, T., Sadikov, A., Nussdorfer, P. The prognostic value of Stathmin-1, S100A2, and SYK
proteins in ER-positive primary breast cancer patients treated with adjuvant tamoxifen monotherapy :
an immunohistochemical study. Breast cancer res. treat., Jul. 2008, vol. 110, no. 2, str. 317-326
Artificial Intelligence Laboratory
GuruCue: Recommender System
Artificial Intelligence Laboratory
Artificial Intelligence Laboratory