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Unit of study_

CSYS5010: Introduction to Complex Systems

Globalisation, rapid technological advances, the development of integrated and distributed systems, cross-disciplinary technical collaboration, and the emergence of "evolved" (as opposed to designed) systems are some of the reasons why many systems have begun to be described as complex systems in recent times. Complex technological, biological, socio-economic and socio-ecological systems (power grids, communication and transport systems, food webs, megaprojects, and interdependent civil infrastructure) are composed of large numbers of diverse interacting parts and exhibit self-organisation and/or emergent behaviour. This unit will introduce the basic concepts of "complex systems theory", and focus on methods for the quantitative analysis and modelling of collective emergent phenomena, using diverse computational approaches such as agent-based modelling and simulation, cellular automata, bio-inspired algorithms, and game theory. Students will gain theoretical knowledge of complex adaptive systems, coupled with practical skills in computational simulation and forecasting using a range of modern toolkits.


Academic unit Civil Engineering
Unit code CSYS5010
Unit name Introduction to Complex Systems
Session, year
Semester 1, 2022
Attendance mode Normal evening
Location Camperdown/Darlington, Sydney
Credit points 6

Enrolment rules

Available to study abroad and exchange students


Teaching staff and contact details

Coordinator Joseph Lizier,
Lecturer(s) Joseph Troy Lizier ,
Michael Stephen Harre,
Type Description Weight Due Length
Assignment group assignment Project report
Report on major project
40% Formal exam period
Due date: 06 Jun 2022 at 23:59
3000 words
Outcomes assessed: LO2 LO3 LO4 LO5 LO6
Assignment Article review
Summarise and critically evaluate an article
10% Week 03 500 words
Outcomes assessed: LO1 LO2 LO4
Assignment group assignment Project proposal
Proposal for major project
25% Week 07
Due date: 06 Apr 2022 at 23:59
1500 words
Outcomes assessed: LO1 LO6 LO5 LO4 LO2
Presentation group assignment Project presentation
Video presentation on major project and answering questions
25% Week 11
Due date: 11 May 2022 at 23:59
15 minutes video, plus Q&A
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6
group assignment = group assignment ?

Article Review: summarise and critically evaluate a credibly-sourced agent-based modelling article in complex systems 

Project proposal, presentation and report: students will work in a group to extend an agent-based model of a real-world complex system, applying feedback at various stages, and producing a report that communicates this development and future pathways (including how they would validate their model).

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (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


High distinction

85 - 100



75 - 84



65 - 74



50 - 64



0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

Penalty clause:


For every calendar day up to and including ten calendar days after the due date, a penalty of 5% of the maximum awardable marks will be applied to late work. The penalty will be calculated by first marking the work, and then subtracting 5% of the maximum awardable mark for each calendar day after the due date. 


Example: Consider an assignment’s maximum awardable mark is 10; the assignment is submitted 2 days late; and the assignment is marked as 7/10. After applying the penalty, marks will be: 7 - (0.5 x 2) = 6/10. 


For work submitted more than ten calendar days after the due date a mark of zero will be awarded. The marker may elect to, but is not required to, provide feedback on such work. 


Refer to section 7A of Assessment procedures policy available at:

For more information see

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

All assessments must be repeated or replaced with different assessment if missed due to special consideration. Extensions for the group Project Presentation will only be granted in the case where formal Special Consideration has been applied for and approved. Furthermore - no late submissions (including with the daily mark deduction) will be accepted for the Project Presentation without Special Consideration.

Special consideration

If you experience short-term circumstances beyond your control, such as illness, injury or misadventure or if you have essential commitments which impact your preparation or performance in an assessment, you may be eligible for special consideration or special arrangements.

Academic integrity

The Current Student website provides information on academic honesty, academic dishonesty, and the resources available to all students.

The University expects students and staff to act ethically and honestly and will treat all allegations of academic dishonesty or plagiarism seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic dishonesty. If such matches indicate evidence of plagiarism or other forms of dishonesty, your teacher is required to report your work for further investigation.

WK Topic Learning activity Learning outcomes
Week 01 What is Complexity? and Modelling complex systems Lecture and tutorial (3 hr) LO1 LO4
Week 02 Introduction to Agent Based Modelling and NetLogo Lecture and tutorial (3 hr) LO1 LO4
Week 03 Extending NetLogo models Lecture and tutorial (3 hr) LO1 LO3 LO4
Week 04 Constructing Agent Based Models in NetLogo Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4
Week 05 Analysing results of NetLogo simulations Lecture and tutorial (3 hr) LO2 LO3 LO4 LO5
Week 06 Dynamical systems I Lecture and tutorial (3 hr) LO1 LO2 LO4 LO5
Week 07 Dynamical Systems II Lecture and tutorial (3 hr) LO1 LO2 LO4 LO5
Week 08 Game Theory Lecture and tutorial (3 hr) LO1 LO5 LO6
Week 09 Genetic Algorithms Lecture and tutorial (3 hr) LO4 LO5 LO6
Week 10 Computation, Information, Order and Randomness I Lecture and tutorial (3 hr) LO1 LO3 LO5 LO6
Week 11 Computation, Information, Order and Randomness II Lecture and tutorial (3 hr) LO1 LO3 LO5 LO6
Week 12 Sharing project videos and feedback Presentation (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 13 Artificial Intelligence overview Lecture and tutorial (3 hr) LO2 LO4 LO5 LO6

Attendance and class requirements

You are expected to attend all (online) classes for this unit. While materials and lecture recordings will be made available these can sometimes fail to work as we would like them to, so it is the student’s responsibility to attend the class in person in order to get the most from this unit of study.

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

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

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.

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

  • LO1. understand and analyse the dynamics of complex systems using intermediate critical analysis skills
  • LO2. analyse and evaluate models of complex systems using scientific programming and the 'Modelling Loop'
  • LO3. Create, using a scientific modelling language such as NetLogo, multi-agent models of complex systems
  • LO4. understand the nature, structure, function and evolution of complex systems and emergent behaviour in multiple different fields
  • LO5. select and apply different approaches to analysing complex systems in different domains (e.g. game theory, dynamical systems, genetic algorithms)
  • LO6. design and evaluate large systems that satisfy structural and functional criteria within given domains and contexts integrating complex systems approaches.

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
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