MPŠ
MPŠ MP&Scaron MP&Scaron MP&Scaron Avtorji

Jožef Stefan
International
Postgraduate School

Jamova 39
SI-1000 Ljubljana
Slovenia

Phone: +386 1 477 31 00
Fax: +386 1 477 31 10
Email: info@mps.si

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Course Description

Network Intelligent Systems and Agents

Program

Information and Communication Technologies, second-level study programme

Lecturers:

prof. dr. Matjaž Gams

Goals:

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.

Content:

Scientific Method:
scientific knowledge structures, scientific
activities/processes.

Introduction:
Definitions of intelligent systems, artificial intelligence, agents.

Information society:
Overview, current state of the art, future directions, natural intelligent systems, inteligentne storitve, computer intelligent systems, artificial intelligence, cognitive science.

Intelligent systems:
Properties, areas, advantages and disadvantages, trends, examples; single systems - expert systems, neural networks, evolutionary algorithms, fuzzy logic, machine learning, data mining, knowledge-based systems; hybrid (multiple) systems.

Intelligent agents:
Properties, areas, overview, advantages and disadvantages, trends, examples, agents’ languages and platforms, MAS, semantic Web and ontologies.

Artificial intelligence:
Properties, areas, overview of AI based on book by Russel and Norvig.

Communication human-computer:
Graphical user interfaces, speech synthesis and recognition, speech understanding, facial recognition, hypermedia, intelligent interfaces, forensic speech and audio analysis, user profiles.

Cognitive sciences:
Overview, cognitive informatics, basic theses of cognitive informatics (Turing test, Church-Turing thesis) and paradoxes (Searle room, Goedel statement), overview of computing mechanisms from the Universal Turing machine on.

Challenges at designing intelligent systems:
The whole SW process of designing systems using artificial intelligence, intelligent systems and agents with the emphasis on specific approaches and dilemmas.

Tools and solutions:
Overview of tools and solutions.

Course literature:

Selected chapters from the following books:

• S. Russel, and P. Norvig. Artificial Intelligence: A Modern Approach, 3rd Edition. Pearson Education Limited, 2009. 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
• D.L. Poole, and A.K. Mackworth. Artificial Intelligence: Foundations of Computational Agents. Cambridge University Press, 2010. ISBN 978-0521519007
• G. Weiss. Multiagent Systems (Intelligent Robotics and Autonomous Agents series). MIT, 2013. ISBN 978-0262018890

Significant publications and references:

• B. Kaluža, B. Cvetković, E. Dovgan, H. Gjoreski, V. Mirchevska, M. Gams, and M. Luštrek. “A Multiagent care system to support independent living.” International journal on artificial intelligence tools, vol. 23, no. 1, pp. 1440001-30, 2014.
• 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. Mirchevska, M. Luštrek, A. Bežek, and M. Gams. “Discovering strategic behaviour of multi-agent systems in adversary settings.” Computing and informatics, 2014, vol. 33, no. 1, pp. 79-108, 2014.
• E. Čuk, M. Gams, R. Piltaver., F. Strle, V. Maraspin-Čarman, and J.F. Tasič. “Intelligent system for diagnosis of erythema migrans.” Applied artificial intelligence, vol. 29, no. 2, pp. 134-147, 2014.
• 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.

Examination:

Seminar work (50%)
Oral defense (50%)

Students obligations:

Seminar work and oral defense.

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