Course - Bio-Inspired Artificial Intelligence - IT3708
Bio-Inspired Artificial Intelligence
Assessments and mandatory activities may be changed until September 20th.
About
About the course
Course content
The main focus of the course is to study intelligent systems inspired by the natural world, in particular biology. Several algorithms and methods are discussed, including evolutionary algorithms. Bio-inspired intelligent systems have thousands of useful applications in fields as diverse as computer science, operations research, machine learning, telecommunications, cybernetics, games, music and art. This course discusses both the theory and practice of bio-inspired artificial intelligence, along with providing some of the basis and inspiration for the different approaches within bio-inspired artificial intelligence.
Learning outcome
Knowledge: The course will give the candidate a general introduction to concepts, methods and algorithms within bio-inspired artificial intelligence.
Skills: The candidate will be able to apply bio-AI methods and algorithms on concrete problems.
General competence: Through theoretical studies and programming projects the candidate shall understand and apply bio-inspired artificial intelligence, and develop a foundation for the application of bio-inspired artificial intelligence to real-world problems.
Learning methods and activities
Lectures, colloquia, self-study, and projects.
Further on evaluation
Grading is based on source code handed in by the student and the student's demonstration and discussion of the code as well as an individual exam. The source code can be handed in and demonstrated by a single student or a group of students.
If there is a complaint about the grade, the student(s) has (have) to redo the demonstration.
In the event of voluntary repetition, fail (F), or valid absence, all course-activities must be retaken in a semester with teaching. Exams are only held in semesters with teaching.
Specific conditions
Admission to a programme of study is required:
Computer Science (MIDT)
Computer Science (MTDT)
Industrial Economics and Technology Management (MTIØT)
Informatics (MSIT)
Recommended previous knowledge
The course builds on TDT4120 Algorithms and Data Structures, TDT4136 Introduction to Artificial Intelligence, TDT4171 Artificial Intelligence Methods, and requires previous knowledge in Discrete Mathematics comparable to MA0301 Elementary Discrete Mathematics and TMA4240 Statistics.
Required previous knowledge
The course is only available for students following a specialization in Artificial Intelligence under the programs MTDT, MIDT, MSIT, MTIØT.
Course materials
To be announced.
Credit reductions
| Course code | Reduction | From |
|---|---|---|
| MNFIT378 | 7.5 sp | |
| MNFIT378 | 7.5 sp | |
| IT8801 | 7.5 sp | Autumn 2008 |
Subject areas
- Informatics
- Technological subjects