Computational Modelling and Simulation (COMP90083)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
From 2023 most subjects will be taught on campus only with flexible options limited to a select number of postgraduate programs and individual subjects.
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Overview
| Availability | Semester 2 - Dual-Delivery |
|---|---|
| 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: 31 January 2024
Eligibility and requirements
Prerequisites
Students must meet one of the following prerequisite options:
Option 1
One of
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| COMP90038 | Algorithms and Complexity |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
12.5 |
| COMP20003 | Algorithms and Data Structures | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
| COMP20007 | Design of Algorithms | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
AND
One of
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| COMP90041 | Programming and Software Development |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
12.5 |
| SWEN20003 | Object Oriented Software Development |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
12.5 |
Option 2
Admission into or selection of one of the following:
- MC-CS Master of Computer Science
- MC-SCICMP Master of Science (Computer Science)
- MC-SOFTENG Master of Software Engineering
- Software specialisation (formal) in the MC-ENG Master of Engineering
- Software with Business specialisation (formal) in the MC-ENG Master of Engineering
- 100pt Program course entry point in the MC-IT Master of Information Technology
- 150pt Program course entry point in the MC-IT Master of Information Technology
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: 31 January 2024
Assessment
| 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% |
5 x Quizzes - 10%. ILOs 1, 2 and 3 are addressed.
| Throughout the teaching period | 10% |
End-of-semester exam, 2 hours. ILO's 1 -3 are addressed in the exam.
| During the examination period | 30% |
Last updated: 31 January 2024
Dates & times
- Semester 2
Coordinator Nic Geard Mode of delivery Dual-Delivery (Parkville) Contact hours 200 hours Total time commitment 200 hours Teaching period 25 July 2022 to 23 October 2022 Last self-enrol date 5 August 2022 Census date 31 August 2022 Last date to withdraw without fail 23 September 2022 Assessment period ends 18 November 2022 Semester 2 contact information
Last updated: 31 January 2024
Further information
- Texts
Last updated: 31 January 2024