Syllabus

Class Times:

Tuesdays and Thursdays 3:30–4:50pm

First class:

January 9, 2024

Location:

CSC B-43

Instructor:

James Wright (james.wright@ualberta.ca)

Office:

ATH 3-57

Office hours:

Available after each class for at least half an hour, and by appointment.

eClass

https://eclass.srv.ualberta.ca/course/view.php?id=95481

Description

This course examines the mathematical and empirical foundations of modelling behaviour by human (and other boundedly rational) agents, in scenarios where the agents have independent goals and priorities. The course will cover the classical game theoretic results for fully rational agents, before surveying the results of modern empirical behavioural research. The course will be capped off by a small research project, in which students will survey an area of existing literature and propose directions for further study.

Topics

1. Game theory
2. Bounded rationality and behavioural game theory
3. Applications of behavioural modelling

Objectives

After taking this course, you should be able to formally represent an arbitrary strategic scenario in the game theoretic paradigm. You should understand the main implications of the full rationality assumption in game theory, and the most common ways in which humans fail to satisfy it.

Readings

The second third of the class will consist of directed readings from the literature. Each lecture will have three assigned readings, each of which will be presented by one student. Every student is required to submit a short summary of the readings before the lecture. Students need not submit a summary of the one paper that they present themselves.

Research survey

The final third of the class will be driven by a small research project, which will be presented to the class. The project can be a survey of the literature of a specific sub-area that we did not cover in class, ideally with a proposed direction for new research. Novel research results are NOT REQUIRED for full marks on the survey, but may be awarded bonus marks.

Each survey will be presented to the class in a workshop-style talk. The project evaluation will be based partly on the project itself, partly on the presentation of the survey, and partly on the quality of the peer review of other students’ presentations.

Grading

Grade breakdown

• Assignments: 30%
• Reading presentation: 15%
• Reading summaries: 15%
• Research survey
  • outline: 5%
  • presentation: 15%
  • writeup: 20%

Late policy

Assignments are to be handed in electronically via eClass by 11:59pm Mountain time on the due date. Assignments may be handed in up to 2 days late, with 20% deducted.

Academic conduct

Submitting the work of another person as your own constitutes plagiarism. The department is very strict about plagiarism and other academic misconduct: ALL forms of cheating are referred to the Dean’s office.

The rules for this course allow consultation collaboration. The specific rules are:

• You may discuss assignments and solutions with your classmates.
• Limit discussion to an informal verbal level. DO NOT exchange written text or source code: you can discuss assignments, but don’t look at each other’s answers or give step-by-step instructions.
• You must list all of the other students that you discussed an assignment with.
• The written part of the assignments must be completed individually.

Texts

• Readings for Part 1 will be from Yoav Shoham and Kevin Leyton-Brown,
  Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, available online.

• Readings for Part 2 will be provided on the schedule.

• For Part 3, students will conduct self-directed readings from the literature.