TDT4171 - Artificial Intelligence Methods

About

Examination arrangement

Examination arrangement: Portfolio assessment
Grade: Letters

Evaluation form Weighting Duration Examination aids Grade deviation
Work 20/100
Written examination 80/100 4 hours D

Course content

This course is a continuation of TDT4136 Introduction to Artificial Intelligence. The three main ways of reasoning (rule-based, model–based, and case-based), will be discussed, with most focus given to model-based reasoning. In particular, we work with reasoning based with uncertain and/or partly missing information, as well as the basis for learning systems (machine learning). The reasoning frameworks that are most prominent in the course are Bayesian networks and decision graphs, but an introduction to neural networks is also included.

Learning outcome

Knowledge:
The candidate will get knowledge of:
- General principles for artificial intelligence (AI)
- Efficient representation of uncertain knowledge
- Decision making principles
- Learning/adaptive systems.

Skills:
- Assess different frameworks for AI in given contexts
- Build systems that realises aspects of intelligent behaviour in computer systems.

General competence:
- Know AI's basis taken from mathematics, logic and cognitive sciences.

Learning methods and activities

Lectures, self study and exercises.

Further on evaluation

The final grade is decided by the final written exam (80%) and exercises (20%).
If there is a re-sit examination, the examination form may be changed from written to oral.
In the case that the student receives an F/Fail as a final grade after both ordinary and re-sit exam, then the student must retake the course in its entirety. Submitted work that counts towards the final grade will also have to be retaken.

Course materials

Stuart Russel, Peter Norvig: Artificial Intelligence. A Modern Approach, Third Edition, Prentice Hall, 2010.
Any additional material will be distributed through the course's webpage.

Credit reductions

Course code Reduction From To
IT2702 3.7 2007-09-01
IT272 3.7 2007-09-01
IT3704 3.7 2008-09-01
MNFIT272 3.7 2007-09-01
MNFIT374 3.7 2008-09-01
MNFIT374 3.7 2008-09-01
SIF8031 3.7 2007-09-01
TDT4170 3.7 2007-09-01

Timetable

Detailed timetable

Examination

Examination arrangement: Portfolio assessment

Term Statuskode Evaluation form Weighting Examination aids Date Time Room *
Spring ORD Work 20/100
Spring ORD Written examination 80/100 D
  • * 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.