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Lecturer(s)
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Olej Vladimír, prof. Ing. CSc.
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Course content
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Knowledge representation. Semantic scheme, frame, inference in semantic scheme. Knowledge representation, search, solution task in state space. Knowledge representation, solution task and planning activity by predicate logic 1. order. Knowledge representation, solution task and planning activity by fuzzy logic. Expert systems. Design diagnostic expert system by AND/OR graph and production rules. Design expert system with uncertainty.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing)
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Learning outcomes
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The aim of the course is to provide basic knowledge in the area of representation knowledge and design knowledge-based and expert systems in binary form and with uncertainty.
The students should be able to design knowledge base for binyry expert sytems and expert sytems with uncertainty.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Oral examination
Completion and successful defense of project from the field of dissertation work.
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Recommended literature
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GIARRATANO J. C., RILEY G. D. Expert Systems: Principles and Programming. PWS Publishing, 1998. ISBN 0534950531.
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JACKSON P. Introduction to Expert Systems. Addison-Wesley, 1999. ISBN 0201876868.
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KELEMEN J., LIDAY M. Expertné systémy pre prax.. SOFA, Bratislava, 1996.
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LEVESQUE H. J., LAKEMEYER G. The Logic of Knowledge Bases.. MIT Press, 2001. ISBN 0262122324.
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NEGNEVITSKY M. Artificial Intelligence : A Guide to Intelligent Systems (2nd Edition).. Addison Wesley, 2004. ISBN 0321204662.
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NILSSON N. J. Artificial Intelligence: A New Synthesis.. Morgan Kaufmann, 1998. ISBN 1558604677.
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OLEJ V., PETR P. Expertní systémy. část I.. Pardubice:Univerzita Pardubice, 1997. ISBN 80-7194-095-X.
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RUSSEL S., NORVIG P. Artificial Intelligence. A Modern Approach.. Prentice Hall, Second Edition, New Jersey, 2003.
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