Artificial Intelligence

Artificial Intelligence

Course title
Artificial Intelligence
Course tag
10295
Semester
3
Course status
Mandatory
ECTS
5
Lectures
30
Practice
15
Independent work
105
Total
150
Teachers and associates
Predrag Šuka, Lecturer
The course aims
Course objectives: to introduce students with basic concepts in the field of artificial intelligence, to learn how to apply artificial intelligence concepts to decision making in games, to learn how to apply artificial intelligence concepts to moving objects and avoid collision in games, and to learn differences in approaches to artificial intelligence in different genres games.
Content
Introduction to Artificial Intelligence. The basics of movement. Kinematic movement. Dynamic behavior in avoiding collision. Coordinated movements. Finding a path. Decision trees. Behavioral trees. Directional acyclic graphs. State machines. Target-driven behavior. Designing artificial intelligence in games.
Literature:
Ian Millington and John Funge: Artificial Intelligence for Games
Supplementary literature

Minimum learning outcomes

  1. Implement simple decision-making computer agent using artificial intelligence
  2. Suggest and implement motion algorithms and computer agents using artificial intelligence
  3. Suggest and implement track finding algorithms in the 2D environment
  4. Suggest and implement collision avoidance algorithms in the 2D environment

Preferred learning outcomes

  1. Implement complex decision-making computer agent based on the default parameters using artificial intelligence
  2. Valorize the influence of algorithm change on behavior of computer agents using artificial intelligence
  3. Suggest and implement track finding algorithms in the 3D environment
  4. Suggest and implement collision avoidance algorithms in the 3D environment