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INFB  Introduction to Knowledge Processing Course INF
Lecturers : Dipl.-Inform. Ingo Boersch    eMail
Prof. Dr. Emanuel Kitzelmann    eMail
Term 4
Course Classification : Bachelor Informatik, Profil-Katalog B-INF-Profil CH 4
Language : Deutsch/Englisch Type VÜ 
Type of examination : PL  Credits
Method of evaluation : written examination 120 min 
Requirements :
Cross References :  
Previous knowledges :  
Aids and special features : Mode of assessment
Pass at course examination
Graded: yes
Continuous Evaluation for assignments.
Overall grade is the course examination grade. 
Teaching aims : Students will know the basics of artificial intelligence (AI) and information processing as well as their practical applications in computer science and media.
They will learn how to apply, construct and implement relevant processes and algorithms, including estimating and judging their performance. 
Contents :

Introduction to AI, search procedures (esp. heuristic), rule-based knowledge representation (forward and backward chaining), derivative tree, conflicts, metarules), logic-based knowledge representation, expert systems and tools, introduction to soft computing, uncertainties and ambiguity, security factors, fuzzy logic, time-knowledge and temporal inference and machine learning. 

Literature : Russell S., Norvig P.: Artificial Intelligence: A Modern Approach, (4th Edition), 2021
Boersch I., Heinsohn J., Socher R.: Wissensverarbeitung - Eine Einführung in die KI, Spektrum, 2. Auflage, 2007
Spreckelsen, C., Spitzer, K.: Wissensbasen und Expertensysteme in der Medizin: KI-Ansätze zwischen klinischer Entscheidungsunterstützung und medizinischem Wissensmanagement, Vieweg+Teubner, 2008
Beierle C., Kern-Isberner G.: Methoden wissensbasierter Systeme: Grundlagen, Algorithmen, Anwendungen. Springer 2014 


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