COMP SCI 4408 - Modelling and Analysis of Complex Systems

North Terrace Campus - Semester 1 - 2020

This course presents an overview of existing theories and methodologies for the analysis of complex systems behaviour. It focuses on the practical application of existing methods to the modelling and analysis of real-life complex systems, and on the identification and analysis of properties such as self-organisation, emergence and adaptability among others.

  • General Course Information
    Course Details
    Course Code COMP SCI 4408
    Course Modelling and Analysis of Complex Systems
    Coordinating Unit Computer Science
    Term Semester 1
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact 2 hours per week
    Available for Study Abroad and Exchange Y
    Prerequisites COMP SCI 2201
    Incompatible COMP SCI 4808
    Assessment Written exam and/or assignments
    Course Staff

    Course Coordinator: A/Prof Claudia Szabo

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:

    1 Develop knowledge of modeling, simulation and analysis techniques aimed at understanding complex systems
    2 Employ various modeling and analysis techniques to real-life complex systems problems.
    3 Read and understand scientific research papers and present them in a seminar talk

    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    Intercultural and ethical competency
    • adept at operating in other cultures
    • comfortable with different nationalities and social contexts
    • able to determine and contribute to desirable social outcomes
    • demonstrated by study abroad or with an understanding of indigenous knowledges
    Self-awareness and emotional intelligence
    • a capacity for self-reflection and a willingness to engage in self-appraisal
    • open to objective and constructive feedback from supervisors and peers
    • able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
  • Learning Resources
    Recommended Resources
    There are no textbooks for this course. However, a number of research papers and other resources will be made available on the course website.
    Online Learning
    More information about the course can be found online on myUni.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    The course aims to introduce students to a wide range of complex systems modeling and analysis terminology, techniques, and processes. The concepts taught in these lectures will be practiced and reinforced by participation in three projects and the reading and reporting on research papers.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    This course is a 3 unit course. The expectation is that students will be spending 12 hours per week working on the course. Students are required to attend weekly lectures; the remainder of the time should be spent working on projects and the research papers. Students are expected to learn the content presented in lectures by doing the projects. They will gain additional knowledge by preparing a presentationthat is based on a research paper and reports that summarizes the research results of the research work they have to present.
    Learning Activities Summary
    The following topics will be covered in the lectures:

    * modeling and simulation techniques: analytical models, agent-based modeling among others
    * complex systems properties: emergence, self-organisation, criticality, adaptability among others
    * metrics and theories to identify complex systems behaviors/properties: micro/macro interactions, entropy among others
    * analysis techniques: regression, ensemble modelling, statistical extrapolation, metrics, decision making, deep learning, fast frugal trees

  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Weighting (%) Individual/ Group Formative/ Summative
    Due (week)*
    Hurdle criteria Learning outcomes CBOK Alignment**
    Practical 1 10 Group Summative week 5 - 6 1. 2.
    Practical 2 10 Group Summative week 8 - 9 1. 2.
    Practical 3 10 Group Summative week 11 - 12 1. 2.
    Research essay 30 Individual Formative week 9 - 11 Min 40% 1. 3.
    Seminar presentation 30 Individual Formative week 6 - 9 Min 40% 1. 3.
    Refection exercises (2) 5 Individual Summative week 7 - 10 1. 2.
    Presentation feeback (2) 5 Individual Summative week 6 -9 1.
    Total 100
    * The specific due date for each assessment task will be available on MyUni.
    This assessment breakdown is registered as an exemption to the University's Assessment for Coursework Programs Policy. The exemption is related to the Procedures clause(s): 1. b. 3.   
    This course has a hurdle requirement. Meeting the specified hurdle criteria is a requirement for passing the course.

    **CBOK is the Core Body of Knowledge for ICT Professionals defined by the Australian Computer Society. The alignment in the table above corresponds with the following CBOK Areas:

    1. Problem Solving
    1.1 Abstraction
    1.2 Design

    2. Professional Knowledge
    2.1 Ethics
    2.2 Professional expectations
    2.3 Teamwork concepts & issues
    2.4 Interpersonal communications
    2.5 Societal issues
    2.6 Understanding of ICT profession

    3. Technology resources
    3.1 Hardware & Software
    3.2 Data & information
    3.3 Networking

    4. Technology Building
    4.1 Programming
    4.2 Human factors
    4.3 Systems development
    4.4 Systems acquisition

    5.  ICT Management
    5.1 IT governance & organisational
    5.2 IT project management
    5.3 Service management 
    5.4 Security management

    Due to the current COVID-19 situation modified arrangements have been made to assessments to facilitate remote learning and teaching. Assessment details provided here reflect recent updates.

    The assessments are unchanged - what changes is the form of delivering the seminar presentation.

    The following modifications have been put in place:-
    Seminar presentations will be uploaded to Youtube and a link sent to me, one day before your allocated seminar presentation slots. A zoom session will take place during your allocated seminar presentation slots. You will be required to join that session and answer any questions from me or your peers.
    Assessment Detail
    Assessment is by way of three programming assignments (practicals) and two presentations and reports of research papers. All assignments will be available on the course website.

    No information currently available.

    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy ( course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

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