OS4VI - Artificial Intelligence

Course specification
Course title Artificial Intelligence
Acronym OS4VI
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 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.
        1. Artificial Intelligence: A Modern Approach. 3rd Edition, S. Russell and P. Norvig. Prentice Hall, 2010 (Original title)
        2. Artificial Intelligence: A New Synthesis, Nils Nilsson, Morgan Kaufmann, 1998 (Original title)
        3. Artificial Intelligence, A guide to Intelligent Systems, 2nd Edition, Michael Negnevitsky, Addison Wesley, 2005 (Original title)
        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 20
        Colloquia 20
        Seminars 0