Course Instructor: Adina Magda Florea

The course covers the theory and practice of artificial intelligence and aims to create a broad view of the discipline and of its main areas of application. By the end of this course, the students will understand the basic principles of artificial intelligence and the associated algorithms, for example informed search, game theory, how to represent and use knowledge, and will get knowledge about artificial intelligence applications, for example automatic planning, natural language processing, theorem proving, machine learning, and the logical language Prolog.

Syllabus:

• Introduction to AI.
• Search methods: uninformed search, informed search.
• Search methods: constraint satisfaction, game playing.
• Symbolic logic.
• Theorem proving.
• Prolog.
• Knowledge representation sing rules.
• Knowledge representation using frames.
• Ontologies.
• Uncertain reasoning: probabilities, the MYCIN model, Bayesian networks.
• Automatic planning.
• Machine learning: induction, knowledge based methods.
• Natural language processing.