Study-Unit Description

Study-Unit Description


TITLE Advanced Artificial Intelligence and Games

UM LEVEL 05 - Postgraduate Modular Diploma or Degree Course



DEPARTMENT Institute of Digital Games

DESCRIPTION The primary goal of the course is to revisit the field of game artificial intelligence (AI) and introduce non-traditional uses of AI in games. A short introduction will be given on AI areas that are currently reshaping the game AI research and development roadmap including procedural content generation, player experience modeling, and AI-based game design. The primary focus of the course will be on player modeling and procedural content generation. In player modeling, the course explores several different topics spanning from game analytics and game data mining to affective computing methods. In procedural content generation, the course explores all the various steps of generating a content starting from the different ways to represent the generated content to evaluating the content generator and visualize its outputs.

The course will cover the topics of player modeling (including model Input, Output, and modeling approaches) and procedural content generation (constructive, search-based and machine-learning approaches).

Study-Unit Aims:

- Introduction to the theory and implementation of player modeling and procedural content generation algorithms;
- Uses of artificial and computational intelligence for modeling users of games and for generating content;

Learning Outcomes:

1. Knowledge & Understanding:

By the end of the study-unit the student will be able to:

- Describe and theorize on the algorithms and domains covered in class;
- Identify tasks that can be tackled through player modeling and procedural content generation methods and select the appropriate method for the problem under investigation;
- Compare the performance of different methods and reflect on their suitability for a domain.

2. Skills:

By the end of the study-unit the student will be able to:

- Design and implement efficient data mining, affect recognition, procedural content generation, modeling and adaptation algorithms;
- Evaluate the algorithms in a commercial-standard application (e.g. game production);
- Work efficiently in groups and evaluate the algorithms in data derived from commercial-standard game productions.

Main Text/s and any supplementary readings:

- Yannakakis and Togelius, "Artificial Intelligence and Games", Springer Nature, 2018.
- Shaker, Togelius, and Nelson, "Procedural Content Generation in Games", Springer International Publishing, 2016.
- Short and Adams, "Procedural generation in game design", CRC Press, 2017.
- Yu, "Spelunky", Boss Fight Books, 2016.
- Karth and Smith. "WaveFunctionCollapse: Content Generation via Constraint Solving and Machine Learning", IEEE Transactions on Games, 2021.
- Snodgrass and Ontanón, "Learning to Generate Video Game Maps using Markov Models", IEEE Transactions on Computational Intelligence and AI in Games, 2016.

Various online articles and textbook chapters.

ADDITIONAL NOTES Pre-requisite Qualifications: Bachelor's in Engineering/CS or related fields; Object-oriented Programming

STUDY-UNIT TYPE Lecture, Tutorial and Project

Assessment Component/s Assessment Due Sept. Asst Session Weighting
Presentation (10 Minutes) SEM2 Yes 10%
Oral Examination (20 Minutes) SEM2 Yes 40%
Report SEM2 Yes 50%

LECTURER/S Ahmed Abdelsamea Hassan Khalifa
Antonios Liapis
Konstantinos Makantasis


The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the description above applies to study-units available during the academic year 2023/4. It may be subject to change in subsequent years.