ARTIFICIAL INTELLIGENCE

The course deals with two basic directions of artificial intelligence: problem solving with search, knowledge representation and reasoning. In the first direction it deals with basic heuristic search algorithms. In the second, it deals with categories of knowledge representation languages, like first-order logic (and its implementation in Prolog), production rules, semantic nets and frames. It also deals with representation of uncertain and fuzzy knowledge. Across above topics, it provides students the opportunity to acquire skills in theoretical and practical levels.

Objectives

The aim of the course is that students, after completing the course, have obtained knowledge about basic concepts of Artificial intelligence and have acquired skills on solving problems using artificial intelligence methods. Basic knowledge and skills are the following: • Representation and solving problems using various search algorithms • Description of knowledge in First Order Predicate Logic • Problem solving with knowledge representation and reasoning • Representation and Problem Solving with logic programming languages • Knowledge representation and solving problems with uncertainty and fuzziness • Knowledge representation and solving problems with semantic networks and frames

Prerequisites

Good programming skills

Syllabus

• Introduction to Artificial Intelligence • State space and Search • Blind Search strategies • Heuristic Search strategies • Knowledge Representation • Logic and Reasoning • Prolog Programming Language • Production Rules • Uncertain Knowledge Representation • Fuzzy Knowledge Representation • Semantic Networks-Frames