BI-ZUM Základy umělé inteligence
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Basic topics focused on symbolic artificial intelligence. These topics covers requirements for the state exam. These topics will be part of the exam in the summer semester of the academic year 2019/2020 provided the exam will take place.

1,2Definitions of artificial intelligence, history, Turing test. Non-informed state-space searchPDF, PDF, PDF
3Informed state-space search: Dijkstra, heuristics, Greedy search, A*PDF, PDF
4Optimization, local search algorithms, QUBOPDF, PDF, PDF
5Automated planning, classical planning, actionsPDF
6Robotics, robotic hardware, motion planningPDF
7Agents, simple decision making, game theory, game tree searchPDF, PDF, PDF
8Problem modeling, CSP, SAT, direct encodingPDF
9Decision making in real non-deterministic environments, MDP, POMDPPDF
10Evolutionary computation, genetic algorithmPDF

Extra material will be included in lectures according to the time constraints.

XEvolutionary ComputationPDF
YData Mining and Machine LearningPDF
ZApriory algorithm, Nearest Neighbor, Naive Bayes, Decision Tree, k-meansPDF
ŽArtificial Neural NetworksPDF, PDF


[1] S. Russell, P. Norvig. Artificial Intelligence: A Modern Approach (Third Edition). ISBN: 978-0136042594. Prentice Hall, 2009.