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The course covers selected areas of artificial intelligence focusing primarily on different approaches to knowledge representation and reasoning both under certainty and uncertainty. In the practical part of the course the emphasis is mainly on rule-based programming in CLIPS and the design of fuzzy logic systems in Matlab.
Last update: Hrnčiřík Pavel (11.08.2013)
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R: Giarratano J.C., Riley G.D.,Expert Systems: Principles and Programming,Course Technology,New York,2004,0534384471 R: Russell S.,Norvig P.,Artificial Intelligence: A Modern Approach,Prentice Hall, Englewood Cliffs,2002,0137903952 R: Ross J.T., Fuzzy Logic with Engineering Applications, Wiley-Blackwell, 2010, ISBN 978-0470743768 R: Passino K.M., Yurkovich S., Fuzzy Control, Addison-Wesley,New York, 1998,020118074X R: Buckley J.J., Eslami E., An Introduction to Fuzzy Logic and Fuzzy Sets (Advances in Intelligent and Soft Computing), Physica, 2008, ISBN 978-3790814477 A: Zadeh L.A., Fuzzy Sets*, Information and Control 8, 338-353 (1965), http://www-bisc.cs.berkeley.edu/Zadeh-1965.pdf Last update: Hrnčiřík Pavel (11.08.2013)
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Během semestru jsou zadávány 2 samostatné projekty, z kterých je pro získání zápočtu nutné získat alespoň 50 % z max. možného bodového ohodnocení. Vlastní zkouška má písemnou formu. Last update: Hrnčiřík Pavel (12.09.2011)
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1 Fuzzy logic. Mamdani - inference method. Sugeno - inference method. 2 Fuzzy controller. Using the Matlab Fuzzy toolbox and Simulink for FC implementation. 3 Individual project - fuzzy controller. 4 Adaptive neuro-fuzzy inference system. 5 Using the fuzzy approach in cluster analysis. 6 Knowledge representation: production systems. 7 Development of expert systems using CLIPS 1. 8 Development of expert systems using CLIPS 2. 9 Knowledge representation - semantic networks, frames. 10 Reasoning under uncertainty. 11 Probabilistic approach for knowledge representation and reasoning. 12 Individual project - knowledge-based system in CLIPS. 13 Individual project - knowledge-based system in CLIPS. 14 Modern trends in artificial intelligence. Last update: TAJ445 (30.09.2013)
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Other study aids: Edward Sazonov: Fuzzy Logic and Applications, course EE509, Clarkson University, Potsdam, NY. http://www.intelligent-systems.info/classes/ee509/ Gary Riley: A Tool for Building Expert Systems. http://clipsrules.sourceforge.net/ Interactive MATLAB & Simulink Based Tutorials, http://www.mathworks.com/academia/student_center/tutorials/index.html?s_tid=acmain_lrn_tut Last update: Hrnčiřík Pavel (11.08.2013)
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Students will be able to: Decide whether a given technical problem can be solved using fuzzy logic control. Design an appropriate fuzzy logic controller for this problem. Propose optimization of its structure. Select an appropriate knowledge representation paradigm for a given technical problem. Design and implement rule-based systems in CLIPS. Last update: Hrnčiřík Pavel (11.08.2013)
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Algorithms and Programming, Artificial Intelligence Last update: TAJ445 (14.12.2013)
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| Teaching methods | ||||
| Activity | Credits | Hours | ||
| Účast na přednáškách | 1 | 28 | ||
| Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi | 0.7 | 20 | ||
| Práce na individuálním projektu | 0.8 | 22 | ||
| Příprava na zkoušku a její absolvování | 1 | 28 | ||
| Účast na seminářích | 0.5 | 14 | ||
| 4 / 4 | 112 / 112 | |||
| Coursework assessment | |
| Form | Significance |
| Regular attendance | 20 |
| Report from individual projects | 30 |
| Examination test | 50 |