Overview
Evolutionary Computation, an area of Artificial Intelligence, comprises machine learning optimisation and classification paradigms based on principles from biological sciences. In this unit, you will explore how principles from theories of evolution and natural selection can be used to construct intelligent systems. You will learn the theoretical concepts of representation, selection, reproduction, and recombination. You will apply evolutionary algorithms, such as evolution strategies, genetic programming, and particle swarm optimisation to tackle science, engineering, social, and business problems and opportunities.
Details
Pre-requisites or Co-requisites
Pre-requisite: COIT20277 Introduction to Artificial Intelligence
Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).
Offerings For Term 1 - 2020
Attendance Requirements
All on-campus students are expected to attend scheduled classes – in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).
Recommended Student Time Commitment
Each 6-credit Postgraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.
Class Timetable
Assessment Overview
Assessment Grading
This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of ‘pass’ in order to pass the unit. If any ‘pass/fail’ tasks are shown in the table above they must also be completed successfully (‘pass’ grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the ‘assessment task’ section (note that in some instances, the minimum mark for a task may be greater than 50%). Consult the University’s Grades and Results Policy for more details of interim results and final grades.
All University policies are available on the CQUniversity Policy site.
You may wish to view these policies:
- Grades and Results Policy
- Assessment Policy and Procedure (Higher Education Coursework)
- Review of Grade Procedure
- Student Academic Integrity Policy and Procedure
- Monitoring Academic Progress (MAP) Policy and Procedure – Domestic Students
- Monitoring Academic Progress (MAP) Policy and Procedure – International Students
- Student Refund and Credit Balance Policy and Procedure
- Student Feedback – Compliments and Complaints Policy and Procedure
- Information and Communications Technology Acceptable Use Policy and Procedure
This list is not an exhaustive list of all University policies. The full list of University policies are available on the CQUniversity Policy site.
- Formulate an evolutionary computation search or optimisation problem by analysing an authentic case or scenario
- Design an evolutionary algorithm for a problem applying the core evolutionary computation concepts and mechanisms
- Build a software application to implement an evolutionary algorithm for a complex search or optimisation problem
- Write an article that evaluates the performance and interprets the results of your software application of evolutionary computation paradigm to an authentic problem.
The Skills Framework for the Information Age (SFIA) standard covers the skills and competencies related to information and communication technologies. SFIA defines levels of responsibility and skills. SFIA is adopted by organisations, governments and individuals in many countries. SFIA is increasingly being used when developing job descriptions and role profiles. SFIA can be used by individuals for creating personal skills profile. The Australian Computer Society (ACS) recognises the SFIA and provides MySFIA for ACS members to build a skills profile.
This unit contributes to the following workplace skills as defined by SFIA 7 (the SFIA code is included):
- Software design (SWDN)
- Programming/software development (PROG)
- Testing (TEST)
- Application Support (ASUP).
Alignment of Assessment Tasks to Learning Outcomes
Assessment Tasks | Learning Outcomes | |||
---|---|---|---|---|
1 | 2 | 3 | 4 | |
1 - Practical Assessment - 25% | ||||
2 - Practical Assessment - 35% | ||||
3 - Written Assessment - 40% |
Alignment of Graduate Attributes to Learning Outcomes
Graduate Attributes | Learning Outcomes | |||
---|---|---|---|---|
1 | 2 | 3 | 4 | |
1 - Knowledge | ||||
2 - Communication | ||||
3 - Cognitive, technical and creative skills | ||||
4 - Research | ||||
5 - Self-management | ||||
6 - Ethical and Professional Responsibility | ||||
7 - Leadership | ||||
8 - Aboriginal and Torres Strait Islander Cultures |
Alignment of Assessment Tasks to Graduate Attributes
Assessment Tasks | Graduate Attributes | |||||||
---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |
1 - Practical Assessment - 25% | ||||||||
2 - Practical Assessment - 35% | ||||||||
3 - Written Assessment - 40% |
Textbooks
There are no required textbooks.
IT Resources
- CQUniversity Student Email
- Internet
- Unit Website (Moodle)
- Anaconda 2019.10
- Python 3.7 or higher
All submissions for this unit must use the referencing styles below:
For further information, see the Assessment Tasks.
m.tom@cqu.edu.au
Module/Topic
Representation, Initialization and Operators in Tree-based Genetic Programming and Introduction to Python
Chapter
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Genetic Programming Preparatory Steps and Pyhton data structures
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Automatically Defined Functions
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Multi-objective Genetic Programming
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Particle Swarm Optimization: First Formulations
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Difficulty and First Results
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Bench Mark Set and Parameter Settings
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Problems and Application
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Introduction to Evolution Strategy
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The Basic ES Algorithm
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Adaptation of Strategy Parameters and co-variance matrix
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Covariance Matrix Adaptation Evolution Strategy
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Unit Coordinator
Dr. Mary Tom
School of Engineering & Technology
Central Queensland University
Brisbane QLD 4000, Australia
Phone: +61 7 3295 1119
Email: m.tom@cqu.edu.au
1 Practical Assessment
In this assignment you will demonstrate your ability to analyse the given scenario, and formulate a Genetic Programming (GP) problem. You will identify the parameters from the given scenario and develop the algorithm. You will design and build the software solution applying GP techniques. This assessment task is to design, code, debug, and test a software application using the topics learnt in Weeks 1 - 4. Further details are in the Assignment 1 specification document available from the Unit website.
Week 6 Thursday (23 Apr 2020) 11:45 pm AEST
Week 8 Thursday (7 May 2020)
- Clear analysis of the given scenario or case study and identify the search or optimization problem
- Correct identification of parameters from the scenario
- Correct GP algorithm applying the principles learnt
- Implementation of a working software solution for the identified problem
- Report documenting testing, and specific aspect of GP as required.
- Formulate an evolutionary computation search or optimisation problem by analysing an authentic case or scenario
- Design an evolutionary algorithm for a problem applying the core evolutionary computation concepts and mechanisms
- Build a software application to implement an evolutionary algorithm for a complex search or optimisation problem
- Knowledge
- Communication
- Cognitive, technical and creative skills
- Self-management
2 Practical Assessment
In this assignment you will demonstrate your ability to analyse the given scenario, and identify the optimization problem. You will model the optimization problem as a Patricle Swarm Optimization (PSO). You will design and build the software solution applying PSO techniques. This assessment task is to design, code, debug, and test a software application using the topics learnt in Weeks 4 - 8. Further details are in the Assignment 2 specification document available from the Unit website.
Week 9 Thursday (14 May 2020) 11:45 pm AEST
Week 11 Thursday (28 May 2020)
- Clear analysis of the given scenario or case study and identify the optimization problem
- Correct identification of parameters from the scenario
- Development of the PSO model
- Implementation of a working software solution for the identified problem
- Report documenting testing, and specific aspect of PSO as required.
- Formulate an evolutionary computation search or optimisation problem by analysing an authentic case or scenario
- Design an evolutionary algorithm for a problem applying the core evolutionary computation concepts and mechanisms
- Build a software application to implement an evolutionary algorithm for a complex search or optimisation problem
- Knowledge
- Communication
- Cognitive, technical and creative skills
- Self-management
- Leadership
3 Written Assessment
In this Assignment you will analyse a solution that applies Evolution Strategies (ES) for an optimization problem. You will evaluate the performance of the solution in comparison to application of PSO and write a report addressing various aspects as required in the Assignment 3 Specification. This assessment task is to assess your understanding of the topics learnt in Weeks 8 - 11. Further details are in the Assignment 3 specification document available from the Unit website.
Week 12 Thursday (4 June 2020) 11:45 pm AEST
Review/Exam Week Friday (12 June 2020)
- Clear analysis of optimization problem
- Clear understanding of the principles of ES
- Comparison of PSO and ES
- Evaluation and correct interpretation of results
- Write an article that evaluates the performance and interprets the results of your software application of evolutionary computation paradigm to an authentic problem.
- Knowledge
- Communication
- Research
- Ethical and Professional Responsibility
As a CQUniversity student you are expected to act honestly in all aspects of your academic work.
Any assessable work undertaken or submitted for review or assessment must be your own work. Assessable work is any type of work you do to meet the assessment requirements in the unit, including draft work submitted for review and feedback and final work to be assessed.
When you use the ideas, words or data of others in your assessment, you must thoroughly and clearly acknowledge the source of this information by using the correct referencing style for your unit. Using others’ work without proper acknowledgement may be considered a form of intellectual dishonesty.
Participating honestly, respectfully, responsibly, and fairly in your university study ensures the CQUniversity qualification you earn will be valued as a true indication of your individual academic achievement and will continue to receive the respect and recognition it deserves.
As a student, you are responsible for reading and following CQUniversity’s policies, including the Student Academic Integrity Policy and Procedure. This policy sets out CQUniversity’s expectations of you to act with integrity, examples of academic integrity breaches to avoid, the processes used to address alleged breaches of academic integrity, and potential penalties.
What is a breach of academic integrity?
A breach of academic integrity includes but is not limited to plagiarism, self-plagiarism, collusion, cheating, contract cheating, and academic misconduct. The Student Academic Integrity Policy and Procedure defines what these terms mean and gives examples.
Why is academic integrity important?
A breach of academic integrity may result in one or more penalties, including suspension or even expulsion from the University. It can also have negative implications for student visas and future enrolment at CQUniversity or elsewhere. Students who engage in contract cheating also risk being blackmailed by contract cheating services.
Where can I get assistance?
For academic advice and guidance, the Academic Learning Centre (ALC) can support you in becoming confident in completing assessments with integrity and of high standard.