Course title
7M9916001
Artificial Intelligence in Games

 TROVATO GABRIELE
Course content
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.
Purpose of class
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.
Goals and objectives
  1. Understanding the concept of AI in gaming experience
  2. Understanding the technical grounds of Machine Learning techniques involved
  3. -
Language
English
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1． Optimisation and games (I) - 0minutes
2． Optimisation and games (II) Review of PowerPoint material 120minutes
3． Guest lecture from videogames industry / academia (I) - 0minutes
4． Introduction to AI (I) Review of PowerPoint material 120minutes
5． Guest lecture from videogames industry / academia (II) - 0minutes
6． Introduction to AI (II) Review of PowerPoint material 120minutes
0minutes
7． Reinforcement Learning Review of PowerPoint material 0minutes
8． Q-Learning Review of PowerPoint material 180minutes
9． Generic Algorithms -
10． Procedural Content Generation Review of PowerPoint material and preparation for test 240minutes
11． Test
12． Test
13． Group work presentation
14． Group work presentation
Total. - - 780minutes
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% -
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 two classes. The content of the group work still has to be decided. 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
Prerequisites
No pre-requisite
Office hours and How to contact professors for questions
  • Wednesday afternoon. Contact in advance.
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
    Active-learning course
    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
    • 4.QUALITY EDUCATION
    Last modified : Sat Sep 09 06:45:41 JST 2023