Assist. Prof. dr. Matej Guid
Assistant
T: +386 1 479 8278
E:Send a message
Office hours: By appointment via email.
Room: R3.69 - Kabinet
Description

Assistant Professor Matej Guid is a researcher in artificial intelligence at the Laboratory for Algorithmics. His work lies at the intersection of machine learning, cognitive science, and computer game playing. In the context of machine learning, he develops methods that enable effective interaction with a domain expert. His central research focus is the study of cognitive processes in human problem solving through algorithmic approaches – in particular, modelling task difficulty for humans, uncovering implicit criteria in expert similarity judgments, and explainable prediction based on search trees. His research also extends to feature construction using explainable predictions, computational creativity, and computer game playing.

Awards
  • Slovenian Start:up of the Year 2020 with the company InstaText, 2020.
  • Prešeren Award for Students for the thesis Computer Analysis of World Chess Champions (supervised by Prof. Dr. Ivan Bratko), 2005.
Classes
Laboratory
Projects
Past projects
Publications

JOURNAL PAPERS

  • B. Vouk, M. Guid, M. Robnik Šikonja. Feature construction using explanations of individual predictions. Engineering applications of artificial intelligence, 2023, vol. 120, str. 1-27, ilustr. ISSN 0952-1976.
  • P. Backus, M. Cubel, M. Guid, S. Sánchez-Pagés, E. López Manas. Gender, competition, and performance: Evidence from chess players. Quantitative economics., 2023, vol. 14, iss. 1, str. 349-380, graf. prikazi. ISSN 1759-7323.
  • K. Reba, M. Guid, K. Rozman, D. Janežič, J. Konc. Exact maximum clique algorithm for different graph types using machine learning. Mathematics, 2022, vol. 10, iss. 1, str. 1-14, ilustr. ISSN 2227-7390.
  • J. Krivec, I. Bratko, M. Guid. Identification and conceptualization of procedural chunks in chess. Cognitive systems research. vol. 69, pp. 22-40, 2021.
  • J. Krivec, M. Guid. The influence of context on information processing. Cognitive Processing, vol. 21, pp. 1-18, 2020.
  • V. Janko, M. Guid. A Program for Progressive Chess. Theoretical Computer Science (2016), doi:10.1016/j.tcs.2016.06.028.
  • D. Hristova, M. Guid, I. Bratko. Assessing the difficulty of chess tactical problems. International journal on advances in intelligent systems, Vol. 7, No. 3/4, pp. 728-738, 2014.
  • A. Iqbal, H. van der Heijden, M. Guid, A. Makhmali. Evaluating the aesthetics of endgame studies: a computational model of human aesthetic perception. IEEE Transactions on Computational Intelligence and AI in Games, Vol. 4, No. 3, pp. 178-191, 2012.
  • M. Guid, I. Bratko. Detecting Fortresses in Chess. Elektrotehniški vestnik: Journal of Electrical Engineering and Computer Science, Vol. 79, No. 1/2, pp. 35-40, 2012.
  • V. Groznik, M. Guid, A. Sadikov, M. Možina, D. Georgiev, V. Kragelj, S. Ribarič, Z. Pirtošek, and I. Bratko. Elicitation of neurological knowledge with argument-based machine learning. Artificial Intelligence in Medicine, Vol. 57, No. 2, pp. 133–144, 2013.
  • M. Guid, I. Bratko. Using Heuristic-Search Based Engines for Estimating Human Skill at Chess. ICGA Journal, Vol. 34, No. 2, pp. 71-81, 2011.
  • M. Guid, A. Pérez, I. Bratko. How Trustworthy is Crafty's Analysis of World Chess Champions? ICGA Journal, Vol. 31, No. 3, pp. 131-144, 2008.
  • M. Guid, I. Bratko. Factors affecting diminishing returns for searching deeper. ICGA Journal, Vol. 30, No. 2, pp. 75-84, 2007.
  • M. Guid, I. Bratko. Computer analysis of world chess champions. ICGA Journal, Vol. 29, No. 2, pp. 65-73, 2006.

 

BOOKS

  • M. Guid. Learn and Master Progressive Chess. Založba UL FRI, 2017.
  • A. Iqbal, M. Guid, S. Colton, J. Krivec, S. Azman, B. Haghighi. The Digital Synaptic Neural Substrate: A New Approach to Computational Creativity. SpringerBriefs in Cognitive Computation, Springer International Publishing, 2016.

 

BOOK CHAPTERS

  • I. Bratko, D. Hristova, M. Guid. Search Versus Knowledge in Human Problem Solving: A Case Study in Chess. In Model-Based Reasoning in Science and Technology, pp. 569–583. Springer International Publishing, 2016.

 

CONFERENCE PAPERS

  • M. Bizjak, M. Guid. Automatic recognition of similar chess motifs. Advances in Computers and Games (ACG 2021).
  • M. Guid, M. Možina, M. Pavlič, K. Turšič. Learning by Arguing in Argument-Based Machine Learning Framework. The 15th International Conference on Intelligent Tutoring Systems (ITS 2019). Kingston, Jamaica, June 3-7, 2019.
  • M. Guid, M. Pavlič, M. Možina. Automated Feedback Generation for Argument-Based Intelligent Tutoring Systems. The 11th International Conference on Computer Supported Education (CSEDU 2019). Heraklion, Crete, Greece, May 2-4, 2019.
  • M. Guid, I. Bratko. Influence of Search Depth on Position Evaluation. The 15th International Conference on Advances in Computer Games (ACG 2017). Leiden, Netherlands, July 3-5, 2017.
  • S. Stoiljkovikj, I. Bratko, M. Guid. A Computational Model for Estimating the Difficulty of Chess Problems. The Annual Third Conference on Advances in Cognitive Systems (ACS 2015), Atlanta, Georgia (USA); 28-31 May, 2015.    
  • V. Janko, M. Guid. Development of a Program for Playing Progressive Chess. The 14th International Conference on Advances in Computer Games (ACG 2015). Leiden, Netherlands, July 1-3, 2015.
  • M. Zapušek, M. Možina, I. Bratko, J. Rugelj, M. Guid: Designing an Interactive Teaching Tool with ABML Knowledge Refinement Loop. Intelligent Tutoring Systems (LNCS 8474): 575-582, 2014.
  • D. Hristova, M. Guid, I. Bratko. Toward modeling task difficulty: the case of chess. COGNITIVE 2014, Venice, Italy, May 25-29, 2014. The Sixth International Conference on Advanced Cognitive Technologies and Applications, pp. 211-214, 2014. IARIA.
  • M. Guid, M. Možina, C. Bohak, A. Sadikov, I. Bratko: Building an Intelligent Tutoring System for Chess Endgames. The 5th International Conference on Computer Supported Education: 263-266, 2013.
  • M. Guid, I. Bratko: Search-Based Estimation of Problem Difficulty for Humans. Artificial Intelligence in Education (LNCS 7926): 860-863, 2013.
  • M. Guid, M. Možina, V. Groznik, A. Sadikov, D. Georgiev, Z. Pirtošek, I. Bratko. ABML Knowledge Refinement Loop: A Case Study. 20th International Symposium, ISMIS 2012, Macau, China, December 4-7, 2012, Proceedings. Lecture Notes in Computer Science, Vol. 7661, pp. 41-50, 2012. Springer.
  • M. Mozina, M. Guid, A. Sadikov, V. Groznik, I. Bratko: Goal-Oriented Conceptualization of Procedural Knowledge. Pp. 286-291, ITS 2012.
  • M. Guid, J. Krivec, and I. Bratko. An experiment in students' acquisition of problem solving skill from goal-oriented instructions. COGNITIVE 2012.
  • M. Možina, M. Guid, A. Sadikov, V. Groznik, J. Krivec and I. Bratko. Conceptualizing Procedural Knowledge Targeted at Students of Different Skill Levels. The 3rd International Conference on Educational Data Mining - EDM, Pittsburg, USA, 2010.
  • M. Možina, M. Guid, J. Krivec, A. Sadikov, and I. Bratko. Learning to Explain with ABML. ExaCt'2010: The 5th International Workshop on Explanation-aware Computing, Lisbon, Portugal, August 16, 2010.
  • M. Guid, M. Možina, A. Sadikov, and I. Bratko. Deriving Concepts and Strategies from Chess Tablebases. Advances in Computers and Games conference - ACG 12, Pamplona, Spain, 2009.
  • J. Krivec, M. Guid, and I. Bratko. Identification and Characteristic Descriptions of Procedural Chunks. COGNITIVE 2009.
  • M. Možina, M. Guid, J. Krivec, A. Sadikov, and I. Bratko. Fighting Knowledge Acquisition Bottleneck with Argument Based Machine Learning. 18th European Conference on Artificial Intelligence – ECAI, 2008.
  • M. Guid, M. Možina, J. Krivec, A. Sadikov, and I. Bratko. Learning Positional Features for Annotating Chess Games: A Case Study. Computers and Games, 6th International Conference, CG 2008, Beijing, China, September/ October, 2008. Proceedings. Computers and Games, Lecture Notes in Computer Science, Vol. 5131, pp. 192-204, 2008. Springer.
  • A. Sadikov, M. Možina, M. Guid, J. Krivec, and I. Bratko. Automated chess tutor. Computers and Games, 5th International Conference, CG 2006, Turin, Italy, May 29-31, 2006. Revised Papers. Computers and Games, Lecture Notes in Computer Science, Vol. 4630, pp. 13-25, 2007. Springer.
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