Artificial Intelligence in Games (3cr)

Evaluation scale

0 - 5

Content scheduling

3. ja 4. perioid. Spring 2026.

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.

Accomplishment methods

Harjoitustehtävät + Harjoitustyö. Kurssin harjoitustyö tehdään Game Programming 2 -kurssin harjoitustyön yhteyteen.

Content

Introduction to game AI
Finite state machines
Path finding
Game genre specific AI techniques
Learning AI
Distributed AI, Team AI and crowd techniques

Location and time

1.1.2026 - 31.5.2026

Materials

Course materials include theoretical content, example code, etc., which will be coded during the lessons.

Recommended literature (not required):
- AI Game Programming Wisdom Volumes 1–4
- Cormen, Thomas H., et al. Introduction to Algorithms. 4th ed., MIT Press, 2022.

Teaching methods

Note: This course is closely related to the course Game Programming 2 (3 ECTS), which is conducted at the same time. The courses are implemented as a joint delivery. The course will be held as in-class teaching. The teaching method is workshop-style, accompanied by theory. The course schedule is designed so that during the 3rd period there will be in-class teaching one day per week, focusing on theory while simultaneously implementing various functionalities and completing class exercises. The 4th period is reserved for independent study, allowing students to finalize remaining tasks and complete the so-called project work, which will be submitted as the final assignment for the courses. The course includes a few assignments to be submitted plus the project work, which together form the basis for the grade in both the Game Programming 2 and Artificial Intelligence in Games courses.

Employer connections

-

Exam schedules

Submission deadline: May 31, 2026.
Resubmission option: By joining the next implementation of the course.

Completion alternatives

-

Student workload

The student is expected to allocate time for attending in-class sessions. Attendance is not mandatory, and absences are not penalized; however, it is strongly recommended to participate in the classes, as missing them may result in falling significantly behind.
In-class teaching: 8 weeks * ~8 hours/week = ~64 hours.
Independent work: approximately 98 hours, including completing course assignments and the project work.

Assessment criteria, satisfactory (1)

The students know and are proficient in the basic concepts of the course.

Assessment criteria, good (3)

The students are able to use the methods they learn during the course appropriately.

Assessment criteria, excellent (5)

The students are able to apply their learning to different tasks in a variety of ways.

Qualifications

Data Structures and Algorithms

Further information

Before attending the course, make sure you meet the prerequisite requirements. The course requires knowledge of C++, so you should have a reasonable command of it. During the first session, a placement test will be conducted to assess your C++ readiness and determine whether you have the necessary skills to succeed in the course.