Computer Science, Advanced Artificial Intelligence, Second Cycle, 7.5 credits

Aims and objectives

General aims for second cycle education

Second-cycle courses and study programmes shall involve the acquisition of specialist knowledge, competence and skills in relation to first-cycle courses and study programmes, and in addition to the requirements for first-cycle courses and study programmes shall

• further develop the ability of students to integrate and make autonomous use of their knowledge
• develop the students' ability to deal with complex phenomena, issues and situations, and
• develop the students' potential for professional activities that demand considerable autonomy, or for research and development work.

(Higher Education Act, Chapter 1, Section 9)

Course objectives

Knowledge and understanding
After the course the participant should

• understand how problem structure relates to the formal properties of the problem, and
• understand the computational bottlenecks of different problem solving algorithms.

Applied knowledge and skills
After the course the participant should be able to

• formulate real-world problems as search problems, and sketch methods to solve them based on uninformed, heuristic and constraint-based search, and
• decide the most appropriate algorithm for solving given problems.

Judgement and approach
After the course the participant should be able to

• make judgments with regards to relevant scientific, societal and ethical aspects, and
• decide whether a given problem is tractable or requires exponential time for automated solving.

Main content of the course

The course will cover the following topics:

• Introduction to intelligent agents,
• problem solving and search: uninformed and informed search strategies,
• constraint reasoning, backtracking search and
• boolean satisfiability, the DPLL algorithm.

Teaching methods

The course is given in the form of lectures and laboratory exercices.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Examination methods

Theory, 4.5 credits (Code: A003)
Written exam.
A retake will be scheduled to take place within eleven weeks of the regular examination.

Laboratory Work, 3 credits (Code: A002)
Individual written reports of laboratory exercices.

For students with a documented disability, the university may approve applications for adapted or other forms of examinations.

For further information, see the university's local examination regulations (in Swedish).

Grades

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may prescribe which grading system shall apply. The grade is to be determined by a teacher specifically appointed by the university (an examiner).

According to regulations on grading systems for first- and second-cycle education (vice-chancellor's decision 2019-01-15, ORU 2019/00107), one of the following grades is to be used: fail, pass, or pass with distinction. The vice-chancellor or a person appointed by the vice-chancellor may decide on exceptions from this provision for a specific course, if there are special reasons.

Grades used on course are Fail (U), Pass (G) or Pass with Distinction (VG).

Theory
Grades used are Fail (U), Pass (G) or Pass with Distinction (VG).

Laboratory Work
Grades used are Fail (U) or Pass (G).

For further information, see the university's local examination regulations (in Swedish).

Comments on grades

The final grade of the course is given by the grade of the theory part, provided that the laboratory part is approved.

Specific entry requirements

First-cycle degree of 180 credits, with Computer Science as the main field of study, and at least 15 credits in mathematics (analysis and algebra). The applicant must also have qualifications corresponding to the course "English 6" or "English B" from the Swedish Upper Secondary School.

OR

First-cycle degree of 180 credits, and at least 30 credits in mathematics (analysis and algebra), as well as at least 15 credits in Computer Science or Informatics (which includes programming). The applicant must also have qualifications corresponding to the course "English 6" or "English B" from the Swedish Upper Secondary School.

For further information, see the university's admission regulations (in Swedish).

Transfer of credits for previous studies

Students who have previously completed higher education or other activities are, in accordance with the Higher Education Ordinance, entitled to have these credited towards the current programme, providing that the previous studies or activities meet certain criteria.

For further information, see the university's local credit transfer regulations (in Swedish).

Other provisions

The course is given in English.

Reading list and other teaching materials

Required Reading

Russell, Stuart and Norvig, Peter 2010, (Third Edition)
Artificial Intelligence, A modern Approach
Prentice Hall

Additional Reading

Dechter, Rina (2003)
Constraint Processing, The Morgan Kaufmann Series in Artificial Intelligence
Elsevier Science

Additional material may be assigned by the teacher.