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BŘEZINA, T.
Originální název
Learning in Mechatronic Conceptions
Typ
článek v časopise - ostatní, Jost
Jazyk
angličtina
Originální abstrakt
Mechatronic conceptions are most frequently characterized as synergistic conjunction of the mechanics, electrotechnics and computer science. Computer science as a platform of the realization of control algorithms especially increasingly runs the soft computing algorithms. Soft computing differs from conventional (hard) computing in the basic principle: it exploits the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The most important components of soft computing are fuzzy logic, neural network theory, probabilistic reasoning, genetic algorithm, chaos theory and parts of machine learning theory. Fundamental issue is that the principal contributions of cited components are complementary, not competitive (leading on hybrid systems creation, etc.). The survey of the most interesting ideas of learning used in soft computing is introduced in this contribution.
Klíčová slova
Q-learning, computer science, control algorithms
Autoři
Rok RIV
2001
Vydáno
1. 12. 2001
ISSN
1210-2717
Periodikum
Inženýrská mechanika - Engineering Mechanics
Ročník
8
Číslo
6
Stát
Česká republika
Strany od
431
Strany do
442
Strany počet
12
BibTex
@article{BUT40192, author="Tomáš {Březina}", title="Learning in Mechatronic Conceptions", journal="Inženýrská mechanika - Engineering Mechanics", year="2001", volume="8", number="6", pages="12", issn="1210-2717" }