Outline

Overview

To think and act strategically, one needs to evaluate the effect of one's actions on the actions of others. As most economic decisions are strategic, such as the decision to lower a price or introduce a new tax, economics, if it is to avoid simplistic models, requires a theoretical framework capable of illuminating strategic behaviour. This unit offers a comprehensive, critical introduction to the theory which purports, not only to satisfy this theoretical need, but also potentially to unify the social sciences: game theory. After examining important concepts of game theory, the unit investigates the repercussions for the theory of bargaining and for the evolution of social institutions.

Unit details and rules

Academic unit	Economics
Credit points	6
Prerequisites ?	ECOS2001 or ECOS2901
Corequisites ?	None
Prohibitions ?	ECOS3901
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Jiemai Wu, jiemai.wu@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam	Final exam Paper-based exam	35%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
In-person written or creative task	Tutorial quiz In each tutorial, you will work with your tutor and peers to complete short questions.	10%	Multiple weeks	20 min	AI prohibited
Outcomes assessed:
Out-of-class quiz	Online Quizzes 4 online quizzes, approximately once every 3 lectures	10%	Multiple weeks	n/a	AI allowed
Outcomes assessed:
Written test	In-semester test Paper-based test during Week 7 lecture time	25%	Week 07 Due date: 17 Apr 2026 at 15:30 Closing date: 17 Apr 2026	1 hour	AI prohibited
Outcomes assessed:
Written work	Creative project proposal Submit a team agreement that details the team's plan for the creative project.	5%	Week 09 Due date: 01 May 2026 at 23:59	Multiple weeks	AI allowed
Outcomes assessed:
Presentation	Creative project You will provide a game-theory-informed strategic recommendation to a client of your choice.	15%	Week 12 Due date: 22 May 2026 at 23:59	Multiple weeks	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy (Schedule 1).

As a general guide, a High Distinction indicates work of an exceptional standard, a Distinction a very high standard, a Credit a good standard, and a Pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an exceptional standard as defined by grade descriptors or exemplars established by the faculty.
Distinction	75 - 84	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a very high standard as defined by grade descriptors or exemplars established by the faculty.
Credit	65 - 74	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a good standard as defined by grade descriptors or exemplars established by the faculty.
Pass	50 - 64	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an acceptable standard as defined by grade descriptors or exemplars established by the faculty.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction to game theory	Lecture (2 hr)
Week 01	Introduction to game theory	Tutorial (1 hr)
Week 02	Static games of complete information	Lecture (2 hr)
Week 02	Static games of complete information	Tutorial (1 hr)
Week 03	Static games of complete information	Lecture (2 hr)
Week 03	Static games of complete information	Tutorial (1 hr)
Week 04	Dynamic games of complete information	Lecture (2 hr)
Week 04	Dynamic games of complete information	Tutorial (1 hr)
Week 05	Dynamic games of complete information	Lecture (2 hr)
Week 05	Dynamic games of complete information	Tutorial (1 hr)
Week 06	Dynamic games of complete information	Lecture (2 hr)
Week 06	Dynamic games of complete information	Tutorial (1 hr)
Week 07	In-semester test	Lecture (1 hr)
Week 09	Static games of incomplete information	Lecture (2 hr)
Week 09	Static games of incomplete information	Tutorial (1 hr)
Week 10	Static games of incomplete information	Lecture (2 hr)
Week 10	Static games of incomplete information	Tutorial (1 hr)
Week 11	Dynamic games of incomplete information	Lecture (2 hr)
Week 11	Dynamic games of incomplete information	Tutorial (1 hr)
Week 12	Dynamic games of incomplete information	Lecture (2 hr)
Week 12	Dynamic games of incomplete information	Tutorial (1 hr)
Week 13	Final Review	Lecture (2 hr)
Week 13	Final Review	Tutorial (1 hr)

Attendance and class requirements

Attendance: According to Faculty Board Resolutions, students in the Faculty of Arts and Social Sciences are expected to attend 90% of their classes. If you attend less than 50% of classes, regardless of the reasons, you may be referred to the Examiner’s Board. The Examiner’s Board will decide whether you should pass or fail the unit of study if your attendance falls below this threshold.
Lecture recording: Most lectures (in recording-equipped venues) will be recorded and may be made available to students on the LMS. However, you should not rely on lecture recording to substitute your classroom learning experience.
Preparation: Students should commit to spend approximately three hours’ preparation time (reading, studying, homework, essays, etc.) for every hour of scheduled instruction.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Game Theory for Applied Economists by Robert Gibbons, Princeton University Press.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. design optimal strategies and make rational predictions in social and business interactions
LO2. examine important concepts of game theory
LO3. Apply models of game theory to analyse strategic aspects of real-world interactions
LO4. Comprehend individual and institutional behaviours from a rational perspective
LO5. Master the necessary mathematical tools for introductory and intermediate game theory

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Adjusted assessment design and weights in response to student performance.

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

ECOS3012: Strategic Behaviour

Semester 1, 2026 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links