Učni načrt predmeta

Predmet:
Inteligentni sistemi in agenti
Course:
Intelligent Systems and Agents
Študijski program in stopnja /
Study programme and level
Študijska smer /
Study field
Letnik /
Academic year
Semester /
Semester
Informacijske in komunikacijske tehnologije, 3. stopnja Inteligentni sistemi in robotika 1 1
Information and Communication Technologies, 3rd cycle Intelligent Systems and Robotics 1 1
Vrsta predmeta / Course type
Izbirni / Elective
Univerzitetna koda predmeta / University course code:
IKT3-631
Predavanja
Lectures
Seminar
Seminar
Vaje
Tutorial
Klinične vaje
work
Druge oblike
študija
Samost. delo
Individ. work
ECTS
30 30 30 210 10

*Navedena porazdelitev ur velja, če je vpisanih vsaj 15 študentov. Drugače se obseg izvedbe kontaktnih ur sorazmerno zmanjša in prenese v samostojno delo. / This distribution of hours is valid if at least 15 students are enrolled. Otherwise the contact hours are linearly reduced and transfered to individual work.

Nosilec predmeta / Course leader:
prof. dr. Matjaž Gams
Sodelavci / Lecturers:
Jeziki / Languages:
Predavanja / Lectures:
Slovenščina, angleščina / Slovenian, English
Vaje / Tutorial:
Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:
Prerequisits:
Vsebina:
Content (Syllabus outline):
Temeljna literatura in viri / Readings:
Cilji in kompetence:
Objectives and competences:
Predvideni študijski rezultati:
Intendeded learning outcomes:
Metode poučevanja in učenja:
Learning and teaching methods:
Načini ocenjevanja:
Delež v % / Weight in %
Assesment:
Seminarska naloga
80
Seminar work
Ustni zagovor
20
Oral defense
Reference nosilca / Lecturer's references:
1. 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.
2. 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.
3. 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.
4. 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.
5. 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.