Artificial Intelligence in GamesLaajuus (3 cr)
Code: KTVP062
Credits
3 op
Objective
Students will have basic knowledge of different AI techniques used in games. Students will be able to select and implement specific AI techniques required in a game.
Content
Introduction to game AI
Finite state machines
Path finding
Distributed AI and crowd techniques
Situation calculus and desision making architectures
Learning AI
Qualifications
Data Structures and Algorithms
Arviointikriteerit, kiitettävä (5)
The students are able to apply their learning to different tasks in a variety of ways.
Assessment criteria, good (3)
The students are able to use the methods they learn during the course appropriately.
Arviointikriteerit, tyydyttävä (1)
The students know and are proficient in the basic concepts of the course.
Enrollment
02.12.2021 - 31.01.2022
Timing
01.01.2022 - 31.07.2022
Number of ECTS credits allocated
3 op
Mode of delivery
Contact teaching
Unit
Teknologia
Teaching languages
- Finnish
Degree programmes
- Bachelor’s Degree in Business Information Technology
Teachers
- Mikko Romppainen
Groups
-
TTK20SPRaaheTTK20SPRaahe
Objective
Students will have basic knowledge of different AI techniques used in games. Students will be able to select and implement specific AI techniques required in a game.
Content
Introduction to game AI
Finite state machines
Path finding
Distributed AI and crowd techniques
Situation calculus and desision making architectures
Learning AI
Evaluation scale
0 - 5
Arviointikriteerit, kiitettävä (5)
The students are able to apply their learning to different tasks in a variety of ways.
Assessment criteria, good (3)
The students are able to use the methods they learn during the course appropriately.
Arviointikriteerit, tyydyttävä (1)
The students know and are proficient in the basic concepts of the course.
Qualifications
Data Structures and Algorithms
Enrollment
01.12.2021 - 31.01.2022
Timing
01.01.2022 - 31.07.2022
Number of ECTS credits allocated
3 op
Mode of delivery
Contact teaching
Unit
Teknologia
Teaching languages
- Finnish
Degree programmes
- Bachelor’s Degree in Business Information Technology
Teachers
- Mikko Romppainen
Groups
-
TTK20SPOTTK20SPO
-
TTK20SPTTK20SP
Objective
Students will have basic knowledge of different AI techniques used in games. Students will be able to select and implement specific AI techniques required in a game.
Content
Introduction to game AI
Finite state machines
Path finding
Distributed AI and crowd techniques
Situation calculus and desision making architectures
Learning AI
Evaluation scale
0 - 5
Arviointikriteerit, kiitettävä (5)
The students are able to apply their learning to different tasks in a variety of ways.
Assessment criteria, good (3)
The students are able to use the methods they learn during the course appropriately.
Arviointikriteerit, tyydyttävä (1)
The students know and are proficient in the basic concepts of the course.
Qualifications
Data Structures and Algorithms