Popis předmětu - AE3B33KUI
Přehled studia |
Přehled oborů |
Všechny skupiny předmětů |
Všechny předměty |
Seznam rolí |
Vysvětlivky
Návod
Výsledek studentské ankety předmětu je zde: AE3B33KUI
AE3B33KUI | Cybernetics and Artificial Intelligence | ||
---|---|---|---|
Role: | P, V | Rozsah výuky: | 2P+2C |
Katedra: | 13133 | Jazyk výuky: | EN |
Garanti: | Zakončení: | Z,ZK | |
Přednášející: | Kreditů: | 5 | |
Cvičící: | Semestr: | L |
Anotace:
The course will enable students to understand the basic concepts, goals and methods of cybernetics and artificial intelligence, and align some individual topics studied in the bachelor stage into the more profound context of the study program. The syllabus contains topics concerned with general aspects of systems and information theory, problem solving and state space search principles, elements of game theory, knowledge and expert systems, elements of decision theory, recognition and machine learning. The most important feature of the course is its unifying conceptual approach to many, at first sight diverse, components of cybernetics and aritifical intelligence.Výsledek studentské ankety předmětu je zde: AE3B33KUI
Cíle studia:
The course will enable students to understand the basic concepts, goals and methods of cybernetics and artificial intelligence, and align some individual topics studied in the bachelor stage into the more profound context of the study program.Osnovy přednášek:
Introduction to cybernetics, systems and models Elements of general systems theory Information, entropy, information transmission, coding - a cybernetic view Algorithmic entropy, decidability Problem solving, the resolution principle Search algorithms, stochastic search Game theory, two-player games Knowledge representation, semantic networks, production systems, frames and scenarios Expert systems, their architecture, uncertain information processing models Decision and classification principles, Bayesian decision making, attributes, attribute space, recognition, cluster analysis Structural recognition, relations to machine perception and image/scene analysis Neural networks and their training, genetic and evolutionary algorithms Machine learning Applications (if timetable allows)Osnovy cvičení:
1. | - | 2. Cybernetic systems lab showcase |
2. | - | 4. Seminar: Probability and entropy |
3. | - | 4. Computer lab: System models |
5. | - | 6. Seminar: Information transmission |
5. | - | 6. Computer lab: Compression algorithms |
6. | - | 10. Seminar: Search |
7. | - | 10. Computer lab: Search |
8. | - | 12. Seminar: Decision making, classification, recognition |
9. | - | 12. Computer lab: Expert systems |
10. | - | 13. Seminar with computer simulation: Evolutionary algorithms, neural networks |
11. | - | 14. Machine learning, class credits |
Literatura:
Nilsson, N. N.: Artificial Intelligence: A New Synthesis. Morgan Kaufmann Publ. San Francisco, 1998Požadavky:
https://cw.felk.cvut.cz/doku.php/courses/a3b33kui/startPoznámka:
Rozsah výuky v kombinované formě studia: 14p+6c |
Webová stránka:
http://cw.felk.cvut.cz/doku.php/courses/ae3b33kui/startKlíčová slova:
Cybernetics, artificial intelligencePředmět je zahrnut do těchto studijních plánů:
Stránka vytvořena 21.1.2021 17:50:30, semestry: Z/2020-1, L/2021-2, L/2020-1, Z/2021-2, připomínky k informační náplni zasílejte správci studijních plánů | Návrh a realizace: I. Halaška (K336), J. Novák (K336) |