Syllabus academic year 2007/2008
APPLIED ARTIFICIAL INTELLIGENCEEDA132

Higher education credits: 7,5. Grading scale: TH. Level: G2 (First level). Language of instruction: The course will be given in Swedish. EDA132 overlap following cours/es: EDA131 och EDA131. Optional for: D3, E3, F3, Pi4. Course coordinator: Eric Astor, Eric.Astor@cs.lth.se, Inst f datavetenskap. Prerequisites: EDA027 Algorithms and Data Structures. Assessment: Written examination. The final grade of the course is based on the result of the written examination and the quality of the compulsory assignments. Parts: 2. Further information: Detailed rules concerning the assignments will be found in the course program. Home page: http://www.cs.lth.se/EDA132.

Aim
To give an introduction to various subdomains of artificial intelligence and to give an orientation about fundamental methods within these domains.

Knowledge and understanding
For a passing grade the student must

· display basic knowledge concerning theories and methods related to the treated subdomains.

Skills and abilities
For a passing grade the student must

· complete a number of assignments based on problems related to the treated subdomains.

Contents
Heuristic search. Game programming. Knowledge based systems. Neural nets. Genetic algorithms. Machine learning based on classification. Intelligent agents.

Literature
Russell, S & Norvig, P: Artificial Intelligence - A Modern Approach, 2nd Ed. Prentice Hall 2003. ISBN: 0-13-080302-2

Parts

Code: 0104. Name: Written Examination.
Higher education credits: 3. Grading scale: TH. Assessment: Written examination. The final grade of the course is based on the result of this examination and on the compulsory assignments. Contents: Written examination.

Code: 0204. Name: Assignments.
Higher education credits: 4,5. Grading scale: UG. Assessment: To pass the course all the compulsory assignments must be approved. Details regarding the compulsory assignments will be found in the course program (syllabus) at the course web site. The final grade of the course is based on the result of the written examination and the quality of the compulsory assignments. Contents: Assignments related to some of the treated subdomains are implemented to give practical experience of difficulties such as computational complexity, scalability and result interpretation.