Agent-based systems

1.

Subject title

Agent-based systems

Агентно-базирани системи

2.

Code

F23L3S073

3.

Study program

Примена на информациски технологии, Софтверско инженерство и информациски системи, Компјутерски науки, Компјутерско инженерство, Интернет, мрежи и безбедност, Software engineering and information systems, Стручни студии за програмирање, Примена на информациски технологии, Софтверско инженерство и информациски системи, Компјутерски науки, Компјутерско инженерство, Интернет, мрежи и безбедност, Информатичка едукација, Software engineering and information systems, Стручни студии за програмирање,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Прв циклус

6.

Academic year / semester

3 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Кире Триводалиев проф. д-р Соња Гиевска

9.

Prerequisites for enrollment

Вештачка интелигенција или Математика 3 или Веројатност и статистика или Бизнис статистика

10.

Subject goals and competencies:

Agent-based modeling offers a natural metaphor for understanding and explaining many phenomena in the domains of biological and social systems – from the evolution and spread of epidemics to segregation and coalition formation. Many systems can be modeled as environments composed of autonomous agents that may communicate, cooperate, negotiate, oppose, be self-interested, or act altruistically. The micro-behavior of agents guided by simple rules can give rise to new qualities and complex phenomena on a macro scale. The aim of the course is to acquaint the student with the agent paradigm for the representation and modeling of systems from different domains (eg games, robots, behavior of social groups). After completing the course, the student is expected to have the ability to design, model and implement or simulate a single-agent or multi-agent system.

11.

Subject content:

1. Vovedni poimi. Apstrakcija na agenti. Poveḱe-agentni sistemi. 2. Nedeterministički agenti 3. Markovi procesi na odlučuvanje 4. Učenje so pottiknuvanje 5. Dlaboko učenje so pottiknuvanje 6. Primeri i oblasti na primena na učenje so pottiknuvanje 7. Primena na teorija na igra vo poveḱe-agentni sistemi - Koordinacija i komunikacija na agenti 8. Strategii za formiranje koalicii, sorabotka, glasanje vo poveḱe agentni sistemi 9. Evolutivna teorija na igra 10. Modeliranje i simulacija Show more Listen 489 / 5,000 Translation results Translation result star_border 1. Introductory terms. Abstraction of agents. Multi-agent systems. 2. Non-deterministic agents 3. Mark`s decision-making processes 4. Learning by prompting 5. Deep learning with encouragement 6. Examples and areas of application of motivational learning 7. Application of game theory in multi-agent systems - Coordination and communication of agents 8. Strategies for forming coalitions, cooperation, voting in multi-agent systems 9. Evolutionary game theory 10. Modeling and simulation

12.

Learning methods:

Предавања со користење на презентации, интерактивни предавања, вежби (користење на опрема и софтверски пакети), тимска работа, пример случаи, поканети гости предавачи, самостојна изработка и одбрана на проектна задача и семинарска работа.

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

30 + 45 + 15 + 15 + 75 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

30 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

45 hours

16.

Other forms of activities

16.1.

Project tasks

15 hours

16.2.

Independent tasks

15 hours

16.3.

Homework

75 hours

17.

Grading method

17.1.

Tests

10 points

17.2.

Seminar work / project (presentation: written and oral)

15 points

17.3.

Activities and learning

10 points

17.4.

Final exam

70 points

18.

Grading criteria (points / grade)

up to 50 points

5 (five) (F)

from 51 to 60 points

6 (six) (E)

from 61 to 70 points

7 (seven) (D)

from 71 to 80 points

8 (eight) (C)

from 81 to 90 points

9 (nine) (B)

from 91 to 100 points

10 (ten) (A)

19.

Condition for signature and taking final exam

Реализирани актибвности 15.2 и 16.1

20.

Language of instruction

Македонски и англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature