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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2024/2025

Probabilistic Models of Artificial Intelligence

The course is not on the list Without time-table
Code Completion Credits Range Language
01UMIN KZ 2 2+0 Czech
Garant předmětu:
Lecturer:
Tutor:
Supervisor:
Department of Mathematics
Synopsis:

The course is devoted to the survey of methods used for uncertainty processing in the field of artificial inteligence. The main attention is paid to so-called graphical Markov models, particularly to Bayesian networks.

Requirements:

Basic course of probabilitz and mathematical statistics

Syllabus of lectures:

1. Introduction to artificial intelligence: problem solving, state spaces, search for solution, algorithm A star, optimality of solution. 2. Uncertainty in artificial intelligence: uncertainty in expert systems, pseudobayesian uncertainty processing in Prospector. 3. Imprecise probabilities: capacities, lower an upper probabilities, coherence, belief functions, possibility measures, credal sets. 4. Conditional independence and its properties: factorization lemma, block independence lemma. 5.Graphical Markov properties: pairwise, local and global Markov properties. 6. Triangulated graphs: graph decomposition, maximum cardinality search, perfect ordering of nodes and cliques, triangularization of graphs, running intersection property, junction trees. 7. Bayesian networks: consistency of distribution represented by a Bayesian network, dependence structure. 8. Computation in Bayesain networks: Shachter algorithm, transformation of Bayesian networks to decomposable models, message passing in junction trees.

Syllabus of tutorials:
Study Objective:

Uncertainty models in artificial inteligence and methods of its processing. Skills: Application of given methods to particular problems.

Study materials:

key references:

[1] P. Hájek, T. Havránek, R. Jiroušek, Uncertain Information Processing in Expert Systems, CRC Press 1992.

key references:

[1] P. Hájek, T. Havránek, R. Jiroušek, Uncertain Information Processing in Expert Systems, CRC Press 1992.

Note:
Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2024-05-18
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