Undergraduate Course: Genetic Algorithms and Genetic Programming (INFR09017)
Course Outline
| School |
School of Informatics |
College |
College of Science and Engineering |
| Course type |
Standard |
Availability |
Available to all students |
| Credit level (Normal year taken) |
SCQF Level 09 (Year 3 Undergraduate) |
Credits |
10 |
| Home subject area |
Informatics |
Other subject area |
None |
| Course website |
http://www.inf.ed.ac.uk/teaching/courses/gagp |
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|
| Course description |
This module teaches you about genetic algorithms (GAs), genetic programming (GP) and other such evolutionary computing (EC) ideas based on the idea of solving problems through simulated evolution. These techniques are useful for searching very large spaces. For example, they can be used to search huge parameter spaces in engineering design and spaces of possible schedules in scheduling. However, they can also be used to search for rules and rule sets, for data mining, for good feed-forward or recurrent neural nets and so on. The idea of evolving, rather than designing, algorithms and controllers is especially appealing in AI. The module will also introduce other biologically inspired algorithms, particularly Ant Colony Optimisation methods.
In this module, you will learn about:
- The practicalities of GAs, GP and EC: how to design an appropriate evolutionary algorithm.
- Some of the underlying theory: how such algorithms work, and what is provable about them.
- Issues of experimental design: how to decide whether it works well.
- Current commercial applications.
- Current research directions. |
Entry Requirements
| Pre-requisites |
|
Co-requisites |
|
| Prohibited Combinations |
|
Other requirements |
Successful completion of Year 2 of an Informatics Single or Combined Degree, or equivalent by permission of the School. The course will involve a modest amount of mathematics in a few places, mainly basic probability and a little statistics.
|
| Additional Costs |
None |
Course Delivery Information
|
| Delivery period: 2010/11 Semester 1, Available to all students (SV1)
|
WebCT enabled: No |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| Central | Lecture | | 1-11 | | 15:00 - 15:50 | | | | | Central | Lecture | | 1-11 | | | | | 15:00 - 15:50 |
| First Class |
First class information not currently available |
|
| Delivery period: 2010/11 Semester 1, Part-year visiting students only (VV1)
|
WebCT enabled: No |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| Central | Lecture | | 1-11 | | | | | 15:00 - 15:50 | | Central | Lecture | | 1-11 | | 15:00 - 15:50 | | | |
| First Class |
Week 1, Monday, 09:00 - 09:50, Zone: Central. This course has been replaced by Natural Computing |
Summary of Intended Learning Outcomes
1 - Understanding of evolutionary computation techniques and their broad applicability to a range of hard problems in search, optimisation and machine learning.
2 - To know when an evolutionary technique is applicable, which one to choose and how to evaluate the results.
3 - To know how to apply an evolutionary technique to a real problem and how to choose the parameters for optimal performance.
4 - Matching techniques with problems, evaluating results, tuning parameters, creating algorithms using inspiration from natural systems. |
Assessment Information
Written Examination 75
Assessed Assignments 25
Oral Presentations 0
Assessment
One practical exercise which usually involves programming in a language of your choice.
If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year.
Visiting Student Variant Assessment
Written Examination 75
Assessed Assignments 25
Oral Presentations 0
Assessment
One practical exercise which usually involves programming in a language of your choice. |
| Please see Visiting Student Prospectus website for Visiting Student Assessment information |
Special Arrangements
| Not entered |
Contacts
| Course organiser |
Dr Richard Mayr
Tel: (0131 6)50 5130
Email: rmayr@staffmail.ed.ac.uk |
Course secretary |
Miss Tamise Totterdell
Tel: 0131 650 9970
Email: t.totterdell@ed.ac.uk |
|
copyright 2010 The University of Edinburgh -
1 September 2010 6:09 am
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