MPŠ MP&Scaron MP&Scaron MP&Scaron Avtorji

Jožef Stefan
Postgraduate School

Jamova 39
SI-1000 Ljubljana

Phone: +386 1 477 31 00
Fax: +386 1 477 31 10


Course Description

Intelligent Systems and Agents


Information and Communication Technologies, third-level study programme


prof. dr. Matjaž Gams
dr. Mitja Luštrek


The goal of the course is to provide general and advanced knowledge of intelligent systems and intelligent agents in relation to artificial intelligence, ambient intelligence and information society. In the introduction, basic concepts, goals, motivations and objectives are presented.
The students who will successfully complete this course will master the basics of intelligent systems and agents and will be capable of applying these systems in solving demanding problems and evaluating their results.


Scientific Method:
scientific knowledge structures, scientific

Motivation, goals, usefulness of intelligence. Definitions of natural, engineering, artificial intelligence. Studies of intelligence. Higher levels of understanding.

Information society:
Definition of information society. Trends of information society, properties, practical examples of use. Dilemmas in the current and future society. Intelligent services and systems in information society.

Artificial intelligence:
Short overview of AI (based on the book by Russel and Norvig).

Intelligent systems:
Principles and motivations of intelligent systems. Intelligent systems in business, engineering, science. Methods and techniques of intelligent systems. Examples of killer applications. Overview or relevant courses at best institutions

Intelligent agents:
Agents as basic ingredients of artificial intelligence. Types of agents. Hierarchy of agents. Platforms and languages. Agent repositories. E-business agents. Overview of world-wide lectures.

Ambient intelligence:
Definition of ambient intelligence. Use of intelligent systems and agents. Approaches to major tasks in ambient intelligence. Examples of applications and systems.

Superintelligence and the principle of multiple knowledge:
Definitions. Indicators. Consequences. Examples of applications.

Challenges when introducing intelligent systems and agents:
Specifics of intelligent systems and agents. Advantages and weaknesses compared to classical approaches.

Course literature:


• S. Russel, and P. Norvig. Artificial Intelligence: A Modern Approach, 3rd Edition. Pearson Education Limited, 2014. ISBN 978-0136042594
• A.A. Hopgood. Intelligent Systems for Engineers and Scientists, 3rd Edition. Taylor and Francis, 2011. ISBN 978-0300097603
• R. Sharda, D. Delen, and E. Turban. Business Intelligence and Analytics: Systems for Decision Support, 10th Edition. Prentice Hall, 2014. ISBN 978-0133050905
• N. Bostrom. Superintelligence: Paths, Dangers, Strategies, Oxford University Press, 2016. ISBN 978-0198739838
• G. Weiss. Multiagent Systems (Intelligent Robotics and Autonomous Agents series). MIT, 2013. ISBN 978-0262018890

Significant publications and references:

• A. Tavčar, D. Kužnar, and M. Gams, “Hybrid multi-agent strategy discovering algorithm for human behavior”. Expert systems with applications, ISSN 0957-4174, vol. 71, pp. 370-382, 2017.
• M. Gjoreski, H. Gjoreski, M. Luštrek, and M. Gams. “How accurately can your wrist device recognize daily activities and detect falls?”. Sensors, ISSN 1424-8220, vol. 16, no. 6, pp. 800-1-800-21, 2016.
• H. Gjoreski, B. Kaluža, M. Gams, R. Milić, and M. Luštrek. “Context-based ensemble method for human energy expenditure estimation.” Applied soft computing, ISSN 1568-4946, vol. 37, pp. 960-970, 2015.
• H. Gjoreski, S. Kozina, M. Gams, M. Luštrek, J.A. Álvarez-García, J.H. Hong, J. Ramos, A.K. Dey, M. Bocca, and N. Patwari. “Competitive live evaluations of activity-recognition systems.” IEEE pervasive computing, vol. 14, no. 1, pp. 70-77, 2015.
• V. Vidulin, M. Bohanec, and M. Gams. “Combining human analysis and machine data mining to obtain credible data relations.” Information sciences, vol. 288, pp. 254-278, 2014.


Seminar work (80%)
Oral defense (20%)

Students obligations:

Seminar work and oral defense.