Research group: Intelligent IT Systems in Private and Public Organisations

The implementation of IT systems is one of the most promising areas for decision-making support. The foundations for ensuring the credibility and effectiveness of the decision-making process are broadly divided into two areas of research: first, how the correct descriptions of situations (sets of relevant statements) should be constructed and, secondly, how the transitions should take place, from one statement to another, so that the correct statements (conclusions) are derived from the correct claims (assumptions).


The theoretical foundations of these areas of research are based on the mathematical logic, theory of algebraic systems, and algorithmics. Part of what is needed to study and create decision-making systems is already well-known. As such: various calculations of sequences for formalizing the derivative works; classical and non-classical interpretation procedures to clarify the truthfulness; algebraic systems used as models for detecting non-contradictory claims, etc. However, to implement these (so-called well-known), logic, algebra and algorithmic tools, a large-scale and complex preliminary work, as a rule, needs to be done. This, unfortunately, inevitable preliminary work must take place on many levels.


At first level, one has to deal with how to translate the (natural language) texts that reflect the thinking of decision makers in a particular area into formulas in a suitable predicate calculus, with relevant (numerical) estimates. At the second level, it will be necessary (on the basis of the relevant texts again) to identify the structure of the transitions that have been implemented in order to make sound decisions. However, on the third level, the challenge is to prove whether the veracity of the descriptions and the reliability of the derivative steps can be determined using relevant, rigorous mathematical tools. In this regard, it has proven that appropriate tools must first be created, theoretically justified their suitability, and checked for realistic applicability. This was the case, for example, with the means of transforming natural language texts. It also provides means for extracting the derivative steps contained in the texts that are the subject of discussion and reasoning. It is interesting to note here that, for several derivative steps, it was also possible to draw up appropriate digital circuits!(Matsak, E.; Lorents, P. (2011). Knowledge in Digital Decision Support System. Universal Access in Human-Computer Interaction. Applications and Services, 6768/2011: HCI International 2011, Orlando, Florida, USA. Springer, 263−271. (Lecture Notes in Computer Science).10.1007/978-3-642-21657-2_28.)


People often make decisions based on similarity. It is based on the belief: it is plausible that similar situations and developments will develop similar situations in the future. As well as the other way around, it is plausible that similar situations may have evolved from similar "past" ones.


However, the questions that need to be addressed in this regard are: how to define the relevant similarity and how to quantify the degree of similarity; what constitutes plausibility and how it relates to the means of appropriate evaluation and comparison; whether and how numerical estimates - for example, numerical estimates of similarity - are attributable to distances, distance or proximity estimates?


The aforementioned areas of concern, the results already obtained, and the ongoing studies have been and will be implemented in quite a number of areas. For example: financial decision-making processes, assessment of business environments in different countries, predictive analysis of adversarial cyber-operations, search for optimal solutions for cyber defense, comparisons of situations leading to conflicts, analysis of IT project failures, etc.


Leadership is steadily moving from an inability of people to machine skills. If we want to "not to leave the train", then we need to shape the proper capabilities of our machines. To do this, the use of existing ones and developing new methods will help us to accomplish this. Particularly answering the following questions:
- which strictly limited linguistic means should describe situations and developments in one or another area of management?
- which derivatives we use in one or another field to move from one statement to another in order to obtain the right management decisions?
- on the basis of which characteristics it is decided that some situations or developments are (sufficiently) similar to others, so that the information obtained from others can be reasonably and effectively implemented?


These would be "big issues", in which more specific research topics will be pursued for a number of doctoral theses.

Selected literature references of the research group:

  • Lorents P. (2018) The similarity of situations and developments. The assessment of similarity. (in Estonian: Situatsioonide ja arengute sarnasus ning selle hindamine.) Monograph (To be published. Approximately 250 pages).
  • Lorents P., Matsak E., Kuuseokk A., Harik D. (2017) Assessing the Similarity of Situations and Developments by Using Metrics. 15 pages. Intelligent Decision Technologies (KES-IDT-17), Vilamoura, Algarve, Portugal, 21-23 June 2017. Springer.
  • Matsak, Erika (2017). Credit Scoring and the Creation of a Generic Predictive Model Using Countries’ Similarities Based on European Values Study. Lecture Notes in Business Information Processing, 276: FinanceCom 2016. Springer Verlag, 114−123.978-3-319-52764-2_9.
  • Alas, Ruth; Übius, Ülle; Lorents, Peeter; Matsak, Erika (2017). Corporate Social Responsibility in European and Asian Countries. JMBI UNSRAT (Jurnal Ilmiah Manajemen Bisnis dan Inovasi Universitas Sam Ratulangi), 4 (1, Jurnal Ilmiah Manajemen, Bisnis dan Inovasi (JMBI)), 1−13.
  • Matsak E., Lehtpuu T., Lorents P. (2015) SyLaR - the system for logic and automated reasoning for situation management decision support systems. INTELLIGENT DECISION TECHNOLOGIES, Sorrento, Italy, 17-19 June 2015. Springer.
  • Lorents, Peeter; Matsak, Erika (2013). Veracity and Convincingness: Sources of Plausibility for Decision Making and Situation Management. Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD): 14th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2013) 1-3 July 2013. Honolulu, HI : IEEE Press, 35−42.10.1109/SNPD.2013.95.
  • Matsak, Erika; Lorents, Peeter (2012). Decision-support systems for situation management and communication through the language of algebraic systems. 2012 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA 2012): CogSima 2012. I.E.E.E. Press, 301−307 . (IEEE Conference Publications ).
  • Alas, R.; Lorents, P.; Übius, Ü.; Matsak, E. (2012). Corporate social responsibility: European and Asian countries comparison. Entrepreneurship in Global Competition. Edit. Sarinastiti, N.; Lengkong, F.; Sintawati, M. Penerbit Universitas Atma Yala – Jakarta, 481−498.