Subject: Knowledge management
Course: Artificial intelligence
ECTS credits: 3
Language: Croatian
Duration: 1 semester
Status: compulsory for students of Information Sciences/ elective for all others
Method of teaching: 1 lecture hour - 1 hour of seminar
Prerequisite: none
Assessment: written report, written and oral exam

Course description:
Introduction. What is Artificial Intelligence? Similarities and differences between natural and artificial intelligence. Cognitive psychology. Turing test.
Problem solving, search methods, heuristics, reasoning and inference, decision-making, planning and machine learning. Knowledge representation, methods of knowledge representation: declarative and procedural representation, semantic networks, scripts and frames. Natural language processing. Phonological, morphological, syntactic and semantic levels. Resolving ambiguities, natural language understanding. Expert systems. Components and functioning of expert systems, application of expert systems in various areas, robotics.
Programming artificial intelligence, AI programming languages (LISP and Prolog)

Course objective:
Introduce the basic concepts of artificial intelligence, present the most important areas of artificial intelligence expert systems, AI programming languages, and methods used in AI.

Quality check and success of the course: Quality check and success of the course will be done by combining internal and external evaluation. Internal evaluation will be done by teachers and students using survey method at the end of semester. The external evaluation will be done by colleagues attending the course, by monitoring and assessment of the course.

Reading list:
1. Fetzer, James: Artificial Intelligence: Its Scope and Limits, Kluwer Academic Publishers, Dordrecht, 1990.
2. Mišljenčević, Duško - Maršić, Ivan: Umjetna inteligencija, Školska knjiga, Zagreb, 1991.

Additional reading list:
1. Russell, Stuart - Norvig, Peter: Artificial Intelligence: A Modern Approach, Prentice Hall, New Jersey, 2003.