This module introduces students to the mathematical study of multiple interactive agent decision making. This is an introduction to Game Theory through notions such as Nash Equilibria and Evolutionary Game Theory. Students will learn Game Theory in an active way through role playing and student-led activities.

• represent games in both Extensive Form and Normal Form.

• understand concepts linked to mixed strategies.

• compute dominant strategies.

• identify best responses.

• define and compute Nash Equilibria.

• understand and carry out backward induction.

• understand concepts of subgame perfection.

• compute equilibria and best responses in repeated games.

• understand concepts of Evolutionary Game Theory

• compute evolutionary Stable Strategies

• model finite population eveolutionary games

Modules will be delivered through blended learning. You will be guided through learning activities appropriate to your module, which may include:

• Weekly face to face classes (e.g. labs, lectures, exercise classes)
• Electronic resources that you work through at your own pace (e.g. videos, exercise sheets, lecture notes, e-books, quizzes)

Students are also expected to undertake self-guided study throughout the duration of the module.

Problem solving, logical thinking, mathematical formulation of real-life situations, programming and communication of mathematics

• Representations and basic concepts.

• Analysing behaviour in static settings.

• Further analysis of extensive form games.

• Repeated games.

• Evolutionary Game Theory.

• Modern research topics