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Computational Modelling and Simulation (COMP90083)
Graduate courseworkPoints: 12.5On Campus (Parkville)
For information about the University’s phased return to campus and in-person activity in Winter and Semester 2, please refer to the on-campus subjects page.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 2
Please refer to the LMS for up-to-date subject information, including assessment and participation requirements, for subjects being offered in 2020.
Overview
Availability | Semester 2 |
---|---|
Fees | Look up fees |
Computers are invaluable tools for modelling and simulating complex systems in a range of real word domains. The complex behaviours exhibited by many biological, social and technological systems - such as epidemics, urban systems and robotics - challenge our ability to predict, analyse and design such systems. Building computational models of these systems can help us better understand their structure and behaviour, and make better decisions about their design and control.
The aim of this subject is to provide students with a solid foundation in the conceptual and technical skills required to design, implement and evaluate computational models of complex systems.
INDICATIVE CONTENT
Topics covered will be selected from:
- the use of models for science, engineering and policy
- dynamical systems analysis
- complexity and emergent behaviour
- agent-based models
- design, communication and evaluation of models
- analysis and visualisation of model behaviour
- case study exemplars of specific types of models, such as:
-
- spatial models (eg, transportation)
- network models (eg, epidemics)
- adaptive models (eg, robotics)
Intended learning outcomes
On completion of this project, the student is expected to be able to:
- Identify and abstract the key features of complex systems from a variety of domains
- Understand the theoretical basis underpinning the analysis of complex systems
- Evaluate and select, amongst different modelling techniques, the most appropriate for analysing specific systems
- Create computational models to analyse the behaviour of complex systems.
Generic skills
- Ability to undertake problem identification, formulation and solution
- Capacity for independent critical analysis and problem-solving, including engaging with unfamiliar problems and identifying relevant strategies
- Ability to analyse models, and self-directed research for modelling approaches
- Intellectual curiosity and creativity, including the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency a model-based analysis.
- Openness to new ideas and unconventional critiques of received wisdom
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
At least one subject from each of the following two lists:
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP90038 | Algorithms and Complexity |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP20003 | Algorithms and Data Structures | Semester 2 (On Campus - Parkville) |
12.5 |
COMP20007 | Design of Algorithms | Semester 1 (On Campus - Parkville) |
12.5 |
and
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP90041 | Programming and Software Development |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
SWEN20003 | Object Oriented Software Development |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
OR
Admission into one of the following courses:
- Master of Computer Science
- Master of Science (Computer Science)
- Master of Engineering (Software)
- Master of Engineering (Software with Business)
MC-IT Master of Information Technology (100 or 150 pt programs only)
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Due to the impact of COVID-19, assessment may differ from that published in the Handbook. Students are reminded to check the subject assessment requirements published in the subject outline on the LMS
Description | Timing | Percentage |
---|---|---|
One individual assignment, requiring approximately 25 - 30 hours of work, due in week 5. Addressing Intended Learning Outcomes (ILO's) 1 and 4.
| Week 5 | 20% |
One staged group research project, done in teams of 2-3, including a proposal, report, and demonstration, requiring approximately 30 -40 hours of work, due in week 8 (proposal) and week 12 (report and demonstration). ILO's 1 - 4 are addressed in this assessment..
| From Week 8 to Week 12 | 40% |
End-of-semester exam, 2 hours, end of semester examination period. ILO's 1 -3 are addressed in the exam.
| During the examination period | 40% |
Last updated: 3 November 2022
Dates & times
- Semester 2
Coordinator Nic Geard Mode of delivery On Campus (Parkville) Contact hours 200 hours Total time commitment 200 hours Teaching period 3 August 2020 to 1 November 2020 Last self-enrol date 14 August 2020 Census date 21 September 2020 Last date to withdraw without fail 16 October 2020 Assessment period ends 27 November 2020 Semester 2 contact information
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
Last updated: 3 November 2022