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Artificial Intelligence (Spring 2010)

Course code : EAIT-U1
ECTS Credits : 7,5 Status : Optional
Revised : 30/01 2009 Written : 07/01 2005
Placement : 5-7 semester Hours per week : 4
Length : 1 semester Teaching Language : Danish if no English students are present
Objective : Artificial Intelligence is a field of computer science concerned with complicated problems that usually require human intelligence.

The goal of the course is to let the students work on such problems.
On completion of the course the student
- can use and explain relevant fields of Artificial
Intelligence: Game-theory, Heuristic search,
Machine learning, Logic programming.
- can evaluate the usability of these methods in a
given problem.
- has practical experience from design and
implementation of complex recursive algorithms.
- has practical experience in analysis of
performance and complexity as well as tuning of
algorithms.
- can document his work in writing as well as in a
debate.
- has practical experience from team-based
projects.
Principal Content : Strategic games are games with well defined rules for the cource of the game, and a strategy for applying these rules with the purpose of winning. Examples are tic-tac-toe, checkers and chess witch are so called perfect-information games, and games with chance ex. back-gammon. Strategic games serves as models for problem solving methods in computer science. Methods that are applied in engineering-tasks such as VLSI design, robot-navigation, jobshop-planning etc.
Contents:
Introduction to Artificial Intelligence.
Problem solving by statespace search: We will analyse and implement algorithms to find way through a maze, shortest paths between cities, planning problems etc.
Design and implementation of a game: We will learn how a computer plays chess, and we will implement our own chess-program, or other game of your own choise. Game theory, algorithm analysis, datastructures.
Introduction to Machine learning - how can a computer program learn from it"s experience, Logic programming and knowledge representation.
Teaching method : First part of the course will be theory and experiments with simple games and problems.
The rest of the course is a team project. Here you will implement a game of you own choice. Until now students have implemented: Chess, Checkers, Reversi, Backgammon, Five-in-a-row and Halma.
Finaly we have a tournament, where the programs compete.
Required prequisites : OOP2
Recommended prerequisites : Good programmering skills in C++, C# or Java.
Type of examination : Oral examination based on assignments
External examiner : Internal
Marking : 7 step scale
Remarks : Oral evaluation based on the project.

Before the exam:
Grouppresentation of the project. Each student will give a 5-10 minutes presentation of a part of the project. These presentations must be different and together they must cover important topics of the project.

Oral exam:
The exam is individual, and allow 10 minutes pr. student. During the exam supervisor and censor will ask questions inspired by the presentation and the projectreport.
Grading follows the official statutory order on the 7-point grading scale.:

12 This grade is given for the excellent performance. The student has accomplished the learning objectives with no or only a few unimportant shortcomings
7 This grade is given for the good performance. The student has accomplished the learning objectives but with some shortcomings.
2 This grade is for the acceptable performance where the student have accomplished the learning goals to an just acceptable degree.

The assesment is based on a general impression of the student with respect to the goals of the course. This will be evaluated from the projectreport, the oral performance as well as the funcionality of the project.
Teaching material : Alison Cawsey: The Essence of Artificial Intelligence. Prentice Hall 1998. ISBN 0-7trinsskala-571779-5
Responsible teacher : Bjørn Klint Christensen , bjchr@dtu.dk