7M991600
1 Artificial Intelligence in Games
Artificial Intelligence is a field that has been linked to games since its very beginning. In the videogames industry nowadays,
AI is a critical aspect in ensuring a successful gameplay experience, although the actual applications of machine learning
are limited. In this course we will see the problems underlying games, and the main techniques that can be applied.
This is an intensive course that will consist in 2 periods classes for a single quarter.
The objectives of this class is to illustrate the challenges, the limitations, and the interesting aspects of the application
of Artificial Intelligence to the field of games.
- Understanding the concept of AI in gaming experience
- Understanding the technical grounds of Machine Learning techniques involved
- -
Relationship between 'Goals and Objectives' and 'Course Outcomes'
|
Exam |
Group work |
Participation |
Total. |
1. |
25% |
15% |
10% |
50% |
2. |
25% |
15% |
10% |
50% |
3. |
|
|
|
0% |
Total. |
50% |
30% |
20% |
- |
|
Class schedule |
HW assignments (Including preparation and review of the class.) |
Amount of Time Required |
1. |
History of videogames |
- |
0minutes |
2. |
Game design and trees |
Review of PowerPoint material |
120minutes |
3. |
Pathfinding and algorithms |
Review of PowerPoint material |
120minutes |
4. |
Guest lecture from videogames industry / academia |
Review of PowerPoint material |
120minutes |
5. |
Reinforcement Learning |
Review of PowerPoint material |
120minutes |
6. |
Test |
Preparation for test |
240minutes |
|
0minutes |
7. |
Tournament |
Group work |
240minutes |
Total. |
- |
- |
960minutes |
Evaluation method and criteria
Evaluation method: exam (50%), group work (30%), participation (20%)
Criteria: at least 60% of total evaluation is required to pass.
The main exam is written and individual. The score is integrated by a group work, which is presented in the last day of class.
The content of the group work is a tournament in which AIs play against each other. Active participation is also counted as
a bonus.
Feedback on exams, assignments, etc.
ways of feedback |
specific contents about "Other" |
Feedback in the class |
|
Textbooks and reference materials
Lectures material provided in class (pdf).
Reference: some excerpts from: Ian Millington, "AI for Games, Third Edition", CRC Press
Office hours and How to contact professors for questions
- Wednesday afternoon. Contact in advance.
Non-regionally-oriented course
Development of social and professional independence
Course by professor with work experience
Work experience |
Work experience and relevance to the course content if applicable |
Applicable |
Worked in a videogames company |
Education related SDGs:the Sustainable Development Goals
Last modified : Fri Mar 22 04:10:08 JST 2024