GAME THEORY WITH APPLICATIONS IN ECONOMICS AND BIOLOGY - 2024/5

Module code: MAT3046

Module Overview

This module introduces the topic of Game Theory and various mathematical techniques used in the analysis of games. Classic examples of games are introduced including those with application in economics and biology. The theoretical backbone is a combination of Calculus, Linear Algebra, Ordinary Differential Equations and, in the case of mixed strategies for games, Probability.

Module provider

Mathematics & Physics

Module Leader

SKELDON Anne (Maths & Phys)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 6

Module cap (Maximum number of students): N/A

Overall student workload

Independent Learning Hours: 69

Lecture Hours: 33

Guided Learning: 15

Captured Content: 33

Module Availability

Semester 2

Prerequisites / Co-requisites

NONE.

Module content

Indicative content includes: 


  • General sum games such as the Prisoner’s Dilemma

  • Zero sum games

  • Finite dynamic games

  • Population games such as the Public Good’s game

  • Replicator dynamics



 

Assessment pattern

Assessment type Unit of assessment Weighting
School-timetabled exam/test In-Semester Test (50 min) 20
Examination End-of-Semester Examination (2 hours) 80

Alternative Assessment

N/A

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate: 


  • Subject knowledge through explicit and implicit recall of key definitions and theorems as well as interpreting this theory.

  • Understanding and application of subject knowledge to solve problems, originating from two-player general-sum games, finite dynamic games and evolutionary games (population / repeated games and replicator dynamics).



Thus, the summative assessment for this module consists of:


  • One in-semester test (50 minutes), worth 20% of the module mark, corresponding to Learning Outcomes 1 to 4.

  • A synoptic examination (2 hours), worth 80% of the module mark, corresponding to Learning Outcomes 1 to 5. 



Formative assessment
There are two formative unassessed courseworks over an 11 week period, designed to consolidate student learning. 

Feedback
Students receive individual written feedback on the formative unassessed coursework and the in-semester test. The feedback is timed so that feedback from the first unassessed coursework assists students with preparation for the in-semester test. The feedback from both unassessed courseworks and the in-semester test assists students with preparation for the end-of-semester examination. This written feedback is complemented by verbal feedback given in lectures. Students also receive verbal and written feedback in office hours.

 

Module aims

  • Introduce students to the way that decisions and strategies can be framed in the language of Game Theory.
  • Illustrate key concepts of introductory Game Theory by considering static two-player general-sum games including special cases such as constant sum / zero sum games. Enable students to analyse such game-based problems using the concept of Nash equilibria.
  • Introduce students to finite dynamic games and methods for analysing such games including backward induction and subgame perfect Nash equilibria and introduce students to population games including games against the field and pairwise context games.
  • Introduce students to replicator dynamics.

Learning outcomes

Attributes Developed
001 Students will demonstrate understanding of the basic principles of Game Theory. K
002 Students will be able to formulate static games in either matrix form or extensive form and understand how to analyse them to find Nash equilibria. KC
003 Students will be able to formulate finite dynamic games and analyse them using the concepts of backward induction and subgame perfect Nash equilibria. KC
004 Students will be able to analyse population games using the concept of evolutionarily stable strategies. KC
005 Students will be able to analyse replicator dynamics using phase plane techniques. KCT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to: 


  • Give a detailed introduction to Game Theory, which requires understanding and studying a range of mathematical techniques, including methods of solution for ordinary differential equations.

  • Ensure experience is gained (through demonstration) of the methods typically used to formulate and solve game theory problems so that students can later apply their own decision-making to formulate and solve game theoretic problems.



The learning and teaching methods include:


  • Three one-hour lectures per week for eleven weeks, with typeset notes to complement the lectures. The lectures provide a structured learning environment. Extra examples, not contained in the notes will be written and worked through on the board (or projector-display). Where appropriate, some of the lecture time will be used to give students Q&A opportunities.

  • There are two unassessed courseworks to provide students with further opportunity to consolidate learning. Students receive individual written feedback on these as guidance on their progress and understanding.



Lectures may be recorded. Lecture recordings are intended to give students the opportunity to review parts of the session that they might not have understood fully and should not be seen as an alternative to attendance at lectures.

 

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: MAT3046

Other information

The School of Mathematics and Physics is committed to developing graduates with strengths in Digital Capabilities, Employability, Global and Cultural Capabilities, Resourcefulness and Resilience and Sustainability. This module is designed to allow students to develop knowledge, skills, and capabilities in the following areas:

Digital Capabilities: The SurreyLearn page for MAT3046 features a dynamic discussion forum where students can pose questions and engage with others using e.g. LaTeX and MathML tools. This enhances their digital competencies while facilitating collaborative learning and information sharing.

Employability: MAT3046 enhances employability by honing critical thinking, problem-solving, and decision-making skills. The enhancing of these skills makes the students valued by employers in diverse professional settings, from business and economics to politics and technology, where understanding and influencing strategic interactions is essential.

Global and Cultural Capabilities: Students enrolled in MAT3046 originate from various countries and possess a wide range of cultural backgrounds. During Q and A sessions in lectures, student engagement in discussions naturally cultivates the sharing of different cultures.

Resourcefulness and Resilience: MAT3046 cultivates resourcefulness and resilience in students through its emphasis on strategic decision-making and adaptability. Students encounter diverse scenarios where they must anticipate and respond to the actions of others. This fosters critical thinking, encouraging creative and adaptive problem-solving skills.

Sustainability: Game theory has relevance in sustainability by addressing conflicts and cooperation in resource management and environmental policies. Understanding game dynamics can lead to more effective and sustainable decisions regarding resource allocation and environmental protection, contributing to long-term sustainability efforts.

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Financial Mathematics BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module
Mathematics with Statistics BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module
Mathematics BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module
Economics and Mathematics BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module
Mathematics with Statistics MMath 2 Optional A weighted aggregate mark of 40% is required to pass the module
Mathematics with Music BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module
Mathematics MMath 2 Optional A weighted aggregate mark of 40% is required to pass the module
Mathematics and Physics BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module
Mathematics and Physics MPhys 2 Optional A weighted aggregate mark of 40% is required to pass the module
Mathematics and Physics MMath 2 Optional A weighted aggregate mark of 40% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2024/5 academic year.