- and
inductive logic programming to
learn relations.
Neural networks, a
subsymbolic approach, had been
pursued from
early days and
reemerged strongly in...
- that
require translation before they can be used. A
cognitive model is
subsymbolic if it is made by
constituent entities that are not
representations in...
-
connectionism and com****tionalism need not be at odds. Smolensky's
Subsymbolic Paradigm has to meet the Fodor-Pylyshyn
challenge formulated by classical...
-
means of symbols; (2)
subsymbolic, on the
neural and ****ociative
properties of the
human brain; and (3)
across the symbolic–
subsymbolic border, including...
- that
cognition is com****tional (see com****tionalism). In contrast,
subsymbolic processing specifies no such a
priori ****umptions,
relying only on emergent...
-
hybrid because it
performs mental operations on both the
symbolic and
subsymbolic levels. For the past few years,
there has been an
increasing discussion...
-
cognitive functions that
connect symbolic verbal,
symbolic nonverbal, and
subsymbolic information,
allowing an
individual to put
words to
emotional experiences...
-
knowledge acquisition methodology Symbolic machine learning algorithms Subsymbolic machine learning algorithms Support vector machines Minimum complexity...
- M****achusetts: MIT Press, ISBNÂ 978-0-262-08153-5. Law,
Diane (1994), Searle,
Subsymbolic Functionalism and
Synthetic Intelligence (PDF). McDermott, Drew (14 May...
- Samani". www.hoomansamani.com.
Retrieved 2015-10-07. The
Symbolic and
Subsymbolic Robotic Intelligence Control System (SS-RICS)
Intelligent Systems Group...
