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Expert Systems
Abbreviation: Load: 30(L) + 0(E) + 0(LE) + 0(CE)
Lecturers in charge: Prof. dr. sc. Nikola Bogunović
Course description: Project oriented course. Fundamentals of automated reasoning and deductive systems. Application of automated reasoning in mathematics, digital systems design (verification of hardware and software) and problem solving. Rule-based expert systems augmented with rule weighting, certainty factors, and fuzzy logic. Applications in technical systems synthesis, diagnostics, and process control. Probabilistic reasoning based on Bayesian belief networks. Applications of Bayesian networks in diagnostics and prediction. Project work involves hands-on experience with prevalent expert system shells (e.g. Otter, CLIPS, FuzzyCLIPS, HuginLite).
Lecture languages: - - -
Compulsory literature:
1. Introduction to expert systems;Jackson, P;1999;Addison Wesley
Recommended literature:
2. Automated reasoning: Introduction and Applications;Wos, L., Overbeek, R., Lusk, E., Boyle;1992;McGraw-Hill
3. Bayesian Networks and Decision Graphs;Jensen, F., V.;2001;Springer Verlag
L - Lectures
E - Exercises
LE - Laboratory exercises
CE - Project laboratory
* - Not graded
Copyright (c) 2006. Ministarstva znanosti, obrazovanja i športa. Sva prava zadržana.
Programska podrška (c) 2006. Fakultet elektrotehnike i računarstva.
Oblikovanje(c) 2006. Listopad Web Studio.
Posljednja izmjena 2014-01-27