Course - Sub-symbolic AI Methods - IT3708
IT3708 - Sub-symbolic AI Methods
About
Examination arrangement
Examination arrangement: Portfolio assessment
Grade: Letters
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| Øving | 75/100 | |||
| Rapport | 25/100 |
Course content
The main focus of the course is to build intelligent systems based on two key natural concepts: the brain, and evolution by natural selection. In computer-science, the analogs for these are artificial neural networks (ANNs) and evolutionary algorithms (EAs). Both methods have thousands of useful applications in fields as diverse as control theory, telecommunications, music and art. This course discusses both methods in great detail along with providing a bit of the biological basis for each.
Learning outcome
Students will get both theoretical and practical programming experience with two of the best known sub-symbolic AI methods: artificial neural networks and evolutionary algorithms.
Learning methods and activities
Regular lectures, homeworks and a projects, along with a take-home final exam. The final grade is based 75% on the homeworks/projects and 25% on the take-home exam.
This course is VERY programming intensive, with each homework taking 2-4 weeks to complete. There are normally 4-5 such homework assignments.
Group work on homeworks is acceptable, but group size cannot
exceed 2 members. The take home exam is to be done individually, with absolutely no discussion with other students. Violation of this rule will result in a failing mark for the course.
Recommended previous knowledge
TDT4120 Algorithms and Data Structures and MA0301 Elementary Discrete Mathematics.
Required previous knowledge
TDT4136 Logic and Reasoning Systems, TDT4110 Information Technology, Introduction and at least one university-level course in mathematics or equivalent.
Course materials
Lecture slides, a textbook (possibly 2). Textbooks are chosen at the beginning of the semester.
Credit reductions
| Course code | Reduction | From | To |
|---|---|---|---|
| IT8801 | 7.5 | ||
| MNFIT378 | 7.5 | ||
| MNFIT378 | 7.5 |
Version: 1
Credits:
7.5 SP
Study level: Second degree level
Term no.: 1
Teaching semester: SPRING 2013
Language of instruction: English
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- Informatics
- Technological subjects
Department with academic responsibility
Department of Computer Science
Examination
Examination arrangement: Portfolio assessment
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Spring ORD Rapport 25/100
-
Room Building Number of candidates - Spring ORD Øving 75/100
-
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"