Artificial Intelligence
2009-2010 - IMT3591 - 10 ECTS

Prerequisite(s)

IMT1031 Fundamental Programming

On the basis of

IMT2021 Algorithmic Methods

Expected learning outcomes

On completion of this course the students will be able to:

• Understand the core techniques used for AI
• Understand how to represent problems, and create algorithms to solve those problems
• Understand more about intelligence and problem solving
• Improved C++ programming ability

Topic(s)

• Path finding
• FSM
• Scripts
• Symbolic AI Techniques
• Logic
• Multi agent systems
• State based search
• Goal directed search
• Genetic Algorithms / Programming
• Neural networks
• Reinforcement learning

Teaching Methods

Lectures
Exercises

Teaching Methods (additional text)

This course will focus on practical implementation of AI concepts. Lectures will introduce a topic area, and students are expected to implement and report on the key concept.

Form(s) of Assessment

Written exam, 4 hours

Grading Scale

Alphabetical Scale, A(best) – F (fail)

External/internal examiner

External examiner

Examination support

1) Calculator
2) Notes taken by the students during lectures and self study.
3) Printed lecture slides
Neither book(s) nor photocopy and scan vs. from the books are allowed.

Teaching Materials

Artificial Intelligence: A Modern Approach, 3rd Edition, Stuart Russell and Peter Norvig, 2009

Additional information

In case there will be less than 5 students apply for the course the form may change to suit the class size.