Artificial Intelligence in GamesLaajuus (3 cr)
Code: TTAP012
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
Assessment criteria, excellent (5)
The students are able to apply their learning in variety of ways to different types of tasks.
Assessment criteria, good (3)
The students are able to use methods they have learnt during the course as required.
Assessment criteria, satisfactory (1)
The students are familiar with and proficient in the basic concepts of the course.
Enrollment
30.12.2024 - 26.01.2025
Timing
01.01.2025 - 31.07.2025
Number of ECTS credits allocated
3 op
Mode of delivery
Contact teaching
Unit
Teknologia
Teaching languages
- Finnish
Degree programmes
- Bachelor’s Degree in Information and Communication Technology
Teachers
- Mikko Romppainen
Groups
-
TTV23SPTTV23SP
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
Assessment criteria, excellent (5)
The students are able to apply their learning in variety of ways to different types of tasks.
Assessment criteria, good (3)
The students are able to use methods they have learnt during the course as required.
Assessment criteria, satisfactory (1)
The students are familiar with and proficient in the basic concepts of the course.
Prerequisites
Data Structures and Algorithms
Enrollment
01.12.2023 - 31.01.2024
Timing
01.01.2024 - 31.07.2024
Number of ECTS credits allocated
3 op
Mode of delivery
Contact teaching
Unit
Teknologia
Teaching languages
- Finnish
Degree programmes
- Bachelor’s Degree in Information and Communication Technology
Teachers
- Mikko Romppainen
Groups
-
TTV22SPTTV22SP
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
Assessment criteria, excellent (5)
The students are able to apply their learning in variety of ways to different types of tasks.
Assessment criteria, good (3)
The students are able to use methods they have learnt during the course as required.
Assessment criteria, satisfactory (1)
The students are familiar with and proficient in the basic concepts of the course.
Prerequisites
Data Structures and Algorithms
Enrollment
01.08.2023 - 30.09.2023
Timing
01.08.2023 - 31.12.2023
Number of ECTS credits allocated
3 op
Mode of delivery
Contact teaching
Unit
Teknologia
Teaching languages
- Finnish
Degree programmes
- Bachelor’s Degree in Information and Communication Technology
Teachers
- Mikko Romppainen
Groups
-
TTV21SPTTV21SP
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
Assessment criteria, excellent (5)
The students are able to apply their learning in variety of ways to different types of tasks.
Assessment criteria, good (3)
The students are able to use methods they have learnt during the course as required.
Assessment criteria, satisfactory (1)
The students are familiar with and proficient in the basic concepts of the course.
Prerequisites
Data Structures and Algorithms
Enrollment
01.08.2022 - 30.09.2022
Timing
01.08.2022 - 31.12.2022
Number of ECTS credits allocated
3 op
Mode of delivery
Contact teaching
Unit
Teknologia
Teaching languages
- Finnish
Degree programmes
- Bachelor’s Degree in Information and Communication Technology
Teachers
- Mikko Romppainen
Groups
-
TTV20SPTTV20SP
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
Assessment criteria, excellent (5)
The students are able to apply their learning in variety of ways to different types of tasks.
Assessment criteria, good (3)
The students are able to use methods they have learnt during the course as required.
Assessment criteria, satisfactory (1)
The students are familiar with and proficient in the basic concepts of the course.
Prerequisites
Data Structures and Algorithms