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13E054VI - Artificial Intelligence

Course specification
Course title Artificial Intelligence
Acronym 13E054VI
Study programme Electrical Engineering and Computing
Module Signals and Systems
Type of study bachelor academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
    ESPB 6.0 Status elective
    Condition non
    The goal This course provides a broad technical introduction and a survey of core concepts of artificial intelligence, including search, knowledge representation, planning, reasoning under uncertainty, fuzzy logic, evolutionary programming and inductive learning.
    The outcome Students will be able to independently analyze different types of artificial intelligence systems. They will learn to apply various algorithms to design artificial intelligence systems using MATLAB.
    Contents
    Contents of lectures The history of artificial intelligence. Problems, problem spaces and search. Production systems. Search strategies: uninformed and heuristic search algorithms. Knowledge representation and automated reasoning. Bayesian networks and learning. Introduction to genetic and evolutionary systems. Basic components of genetic algorithms. Typical application.
    Contents of exercises Exercises on computers with a demonstration of algorithms for the design of artificial intelligence systems. System design for search, learning and fuzzy logic. Solve practical problems in various fields of engineering with artificial intelligence approach using MATLAB.
    Literature
    1. Artificial Intelligence: A Modern Approach. 3rd Edition, S. Russell and P. Norvig. Prentice Hall, 2010
    2. Artificial Intelligence: A New Synthesis, Nils Nilsson, Morgan Kaufmann, 1998
    3. Artificial Intelligence, A guide to Intelligent Systems, 2nd Edition, Michael Negnevitsky, Addison Wesley, 2005
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    3 1 1
    Methods of teaching oral lectures, exercises on the computer
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures 0 Test paper 0
    Practical lessons 20 Oral examination 40
    Projects
    Colloquia 20
    Seminars 20