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Artificial intelligence

Code: 45688
ECTS: 5.0
Lecturers in charge: prof. dr. sc. Luka Grubišić - Lectures
Lecturers: prof. dr. sc. Luka Grubišić - Exercises
English level:

1,0,0

All teaching activities will be held in Croatian. However, foreign students in mixed groups will have the opportunity to attend additional office hours with the lecturer and teaching assistants in English to help master the course materials. Additionally, the lecturer will refer foreign students to the corresponding literature in English, as well as give them the possibility of taking the associated exams in English.
Load:

1. komponenta

Lecture typeTotal
Lectures 30
Exercises 15
* Load is given in academic hour (1 academic hour = 45 minutes)
Description:
COURSE AIMS AND OBJECTIVES: The aim is to give broad survey of the AI field and its application.

COURSE DESCRIPTION AND SYLLABUS:
1. Introduction to Artificial Intelligence (AI). What is AI? What is intelligence? Sub-fields of AI research. Evaluation methods: Turing test and Searle's Chinese room. Development of AI. Symbolic approach and connectionism. AI today. Taxonomy of the knowledge representations schemes.
2.Solving problems by searching state space. Informed search and exploration. Heuristic functions. A*.
3. Mathematical logic and automatic theorem proving. Syntax and semantics of knowledge representation schemes. Propositional logic and First-Order logic. Resolution rules. Strategies.
4. Introduction to natural language processing.
5. Expert systems. Production rules. Structure and elements of the ES. Components of ES. Forward and backward chaining. Examples of ES.
6. Introduction to neural networks. Artificial and biological neuron. Neural network definition. NN learning. Neural networks architectures and learning methods.
7. Representing uncertain knowledge. Probabilistic reasoning. Dempster-Shafer theory.
Fuzzy logic and approximate reasoning.
Literature:
1. semester
Mandatory course - Mandatory studij - Computer Science and Mathematics
Consultations schedule: