School of Computer Science BCS accreditation 2021 - 2026

Artificial Intelligence MEng (Hons) - COMP34120 AI and Games

2.1.1 Knowledge and understanding of facts, concepts, principles & theories

This is a full-year course on game theory and computational game theory. It has a large practical component which consists of two substantial projects: one is to design and implement an agent which connects to a game engine and plays a particular board game against other agents. The second is to design an agent which predicts the price which will be set by another agent in order to optimize economic benefit. The theories of games, economic games, mechanism design, and solving such games, including the use of machine learning approaches, are presented in lectures and documents, and is assessed by examination. The practical implementation of these concepts are assessed through group project work. In each semester, the knowledge (the lectures) comes in the first half; the practical implementation comes in the second half.

Assesement : Examination, Lab work

2.1.2 Use of such knowledge in modelling and design

In each project, the students have to use the knowledge from the course to design and implement their solutions. They will not be able to succeed without that knowledge. Modelling the actions of other agents is essential.

Assesement : Examination, Lab work

2.1.3 Problem solving strategies

The group project work is done largely from scratch. Particularly for the first project, there are multiple ways to do it.

Assesement : Lab work

2.1.5 Deploy theory in design, implementation and evaluation of systems

The knowledge concerning how to solve games in the contexts of the two practical projects is highly theoretical. The students design and implement solutions based on that theory. The students will not achieve successful results without making use of the theory that they learned.

Assesement : Lab work

2.1.6 Recognise legal, social, ethical & professional issues

Game theory can help in understanding the incentives for behaving in an unethical or antisocial manner. Computational game theory, and particularly mechanism design can provide incentives against dishonest behavior. These topics are part of the theoretical content of the course.

Assesement : Examination

2.1.7 Knowledge and understanding of commercial and economic issues

The second semester of the course is about economic application of games. The project is about setting prices to maximize profit by predicting the behavior of other players in the market.

Assesement : Examination, Lab work

2.1.8 Knowledge of management techniques to achieve objectives

Only indirectly. The projects are substantial and are done in small groups. The students have to manage the projects themselves.

Assesement : Lab work

2.2.1 Specify, design or construct computer-based systems

In doing the two projects, the students have to specify, design, and implement computer-based agents largely from scratch.

Assesement : Lab work

2.2.2 Evaluate systems in terms of quality and trade-offs

Again it is indirect. The students have procedures whereby they can test their solutions. This allows them to test the efficacy of the decisions they have made.

Assesement : Lab work

2.3.1 Work as a member of a development team

The students work in small groups to develop their agents.

Assesement : Lab work

2.3.2 Development of general transferable skills

The students are required to work in teams, so teamwork is reinforced through practice. Time management is reinforced by the requirement a rough plan by the second week, and by the requirement of a journal. Communication skills are reinforced by the requirement of a group presentation and a final report in the journal.

Assesement : Lab work

3.1.4 Knowledge and understanding of mathematical and/or statistical principles

Game theory is a mathematical subject. Students must understand it and put it into practice.

Assesement : Examination, Lab work

3.2.2 Defining problems, managing design process and evaluating outcomes

Many students do a lot of research in order to design the agent used in the first project. There are many ways to create an agent to play two-player games, and also a literature on the particular game. The students are highly motivated to create the best agent which beats the other agents, and succeed by finding appropriate literature.

Assesement : Lab work

4.1.1 Knowledge and understanding of scientific and engineering principles

The students are encouraged to evaluate their solutions in order to improve them.

Assesement : Lab work

4.1.2 Knowledge and understanding of mathematical principles

The students must understand the mathematical principles of game theory and also a bit of machine learning prediction to succeed with the projects.

Assesement : Lab work

4.1.3 Knowledge and understanding of computational modelling

Computational game theory, which is what this course is about, is intrinsically about computational modelling.

Assesement : Examination, Lab work