MA301      Half Unit
Game Theory I

This information is for the 2021/22 session.

Teacher responsible

Prof Bernhard Von Stengel COL 4.12

Availability

This course is available on the BSc in Business Mathematics and Statistics, BSc in Data Science, BSc in Management, BSc in Mathematics and Economics, BSc in Mathematics with Economics, BSc in Mathematics, Statistics and Business and BSc in Psychological and Behavioural Science. This course is available as an outside option to students on other programmes where regulations permit. This course is available with permission to General Course students.

This course cannot be taken with MA300 Game Theory.

Pre-requisites

The course emphasises a formal treatment of mathematical Game Theory through definitions, theorems and proofs. Familiarity with a rigorous treatment of mathematics is expected. Basic knowledge of matrices and continuity as covered in Mathematical Methods (MA100) or Quantitative Methods (MA107) as well as some knowledge of probability is required.

Course content

Concepts and methods of mathematical game theory. Nim and combinatorial games. Congestion games. Games in strategic form, dominated strategies, Nash equilibrium. Cournot quantity competition. Game trees with perfect information, backward induction. Commitment. Expected utility. Mixed equilibrium. Zero-sum games, maxmin strategies. Extensive games with information sets, behaviour strategies, perfect recall. Bargaining. Geometry of equilibria.

Teaching

This course is delivered through a combination of classes and lectures totalling a minimum of 30 hours across Michaelmas Term. This year, some or all of this teaching will be delivered through a combination of virtual classes and lectures delivered as online videos.

Formative coursework

Written answers to set problems will be expected on a weekly basis.

Indicative reading

Required text: B von Stengel, Game Theory Basics. Cambridge University Press, 2021.

Assessment

Exam (90%, duration: 2 hours) in the summer exam period.
Coursework (10%).

Weekly exercises will be set and marked, and count as coursework.

Course selection videos

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.

Important information in response to COVID-19

Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: Mathematics

Total students 2020/21: 55

Average class size 2020/21: 9

Capped 2020/21: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Self-management
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills