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13M081VINT - Artificial Intelligence

Course specification
Course title Artificial Intelligence
Acronym 13M081VINT
Study programme Electrical Engineering and Computing
Module
Type of study master academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
    ESPB 6.0 Status elective
    Condition
    The goal Familiarize students with basic concepts of artificial intelligence, its subfields and applications in mathematics, computer science and electrical engineering.
    The outcome Student is capable to recognize and solve some electrical engineering problems and computer science problems using appropriate ideas, techniques and methods of artificial intelligence.
    Contents
    URL to lectures https://teams.microsoft.com/l/team/19%3ai7idNjomu45FYaOX1EUOTqM-dWh9LZETW9QxWp6o6Ds1%40thread.tacv2/conversations?groupId=dd491d3a-a6a3-4a34-adf2-defa87903a51&tenantId=1774ef2e-9c62-478a-8d3a-fd2a495547ba
    Contents of lectures Artificial intelligence - overview of history and application areas. Intelligent systems and problem solving. Knowledge, reasoning, planning. Uncertain knowledge and planning. Automated reasoning and acting. Machine learning and teaching. Communicating, observing and acting - elements of robotics.
    Contents of exercises Solving diverse problems related to the theoretical component of the course.
    Literature
    1. S. Russel, P. Norvig: "Artificial Intelligence - A Modern Approach", the 3rd Edition, Prentice Hall, Englewood Cliffs, New Jersey, 2009.
    2. Tsang E.P.K.:"Foundations of Constraint Satisfaction", edited by Thom Fruehwirth, Books on Demand, 2014.
    3. L. Wos at all: " Automated Reasoning: Intoroduction and Applications" McGraw-Hill, 1992.
    4. L. Wos: " Journal of Automated Reasoning, Special Issue: Advances in Logic Through Automated Reasoning" , L. Wos, ed., Vol. 27, No. 2, 2001.
    5. G. Luger, W. A. Stubblefield: " Artificial Intelligence: Structures and Strategies for Complex Problem Solving", The Benjamin/Cummings PublishingCompany, Inc. 1993.
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    3 1
    Methods of teaching Lectures, exercises with solving problems, homeworks, discussions.
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures 0 Test paper 30
    Practical lessons 20 Oral examination 0
    Projects
    Colloquia
    Seminars 50