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Fundamentals of Artificial Intelligence

Interactive Syllabus

Fundamentals of Artificial Intelligence

Exact and approximate inference. Time and uncertainty.

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https://is.muni.cz/el/fi/podzim2022/IV126/um/6.pdf

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Fundamentals of Artificial Intelligence
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  Slides from all lectures in one file
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  Introduction to Artificial Intelligence. Search and metaheuristics: concepts, introduction to single-solution based metaheuristics.
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  Single-solution based metaheuristics.
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  Population-based metaheuristics.
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  Formalization of planning problems, representations. State space planning: forward search.
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  State space planning: backward search. Probability theory (short revision). Bayesian networks.
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  Exact and approximate inference. Time and uncertainty.
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  Test in a written form (10.11.2022)
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  Utility theory, decision networks. Sequential decision problems.
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  Value and policy iteration. Robots, robotic perception. Planning: configuration space.
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  Robotics: motion planning and control
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  Exercises with solutions

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