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The course covers uncertainty in artificial intelligence, decision making, and basic methods of machine learning.
Last update: Barták Roman, prof. RNDr., Ph.D. (05.06.2017)
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To learn the following techniques of artificial intelligence: uncertainty reasoning, decision making, machine learning. Last update: Barták Roman, prof. RNDr., Ph.D. (06.10.2017)
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The course is concluded by an oral exam, that could be, in exceptional cases, in an on-line form. Last update: Barták Roman, prof. RNDr., Ph.D. (28.04.2020)
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S. Russell, P. Norvig: Artificial Intelligence; A Modern Approach, 2003 V. Mařík, O. Štepánková, J. Lažanský a kol.: Umělá Inteligence, 1-6. Academia, Praha Last update: Barták Roman, prof. RNDr., Ph.D. (06.10.2017)
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lectures Last update: Barták Roman, prof. RNDr., Ph.D. (06.10.2017)
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The exam consists of a written preparation and an oral part. The requirements are given by the course syllabus. Last update: Barták Roman, prof. RNDr., Ph.D. (06.10.2017)
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Uncertainty reasoning: probabilistic methods, Bayesian networks, Markov models.
Decision making: utility theory, Markov Decision Processes, decisions with multiple agents, (inverse) game theory.
Machine learning: supervised learning, decision trees, regression, SVM, boosting; version space search; learning probabilistic models, the EM algorithm; reinforcement learning. Last update: Barták Roman, prof. RNDr., Ph.D. (05.06.2017)
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