course-details-portlet

IT3708

Bio-Inspired Artificial Intelligence

Choose study year
Credits 7.5
Level Second degree level
Course start Spring 2025
Duration 1 semester
Language of instruction English
Location Trondheim
Examination arrangement Aggregate score

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.

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 actual methods and algorithms. 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 a source code handed in by the student and his/her demonstration of the code, and an individual exam.

If there is a complaint against the grade the student has 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.

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
This course has academic overlap with the courses in the table above. If you take overlapping courses, you will receive a credit reduction in the course where you have the lowest grade. If the grades are the same, the reduction will be applied to the course completed most recently.

Subject areas

  • Informatics
  • Technological subjects

Contact information

Course coordinator

Lecturers

Department with academic responsibility

Department of Computer Science