This book offers a model for concepts and their dynamics. A
basic assumptionis that concepts are composed of specified
components, which are representedby large binary patterns
whose psychological meaning is governed by the interaction
between conceptual modules and other functional modules. A
recurrent connectionist model is developed in which some
inputs are attracted faster than others by an attractor,
where convergence times can beinterpreted as decision
latencies. The learning rule proposed is extracted from
psychological experiments. The rule has the property that
that whena context becomes more familiar, the associations
between the concepts of the context spontaneously evolve
from loose associations to a more taxonomicorganization.
basic assumptionis that concepts are composed of specified
components, which are representedby large binary patterns
whose psychological meaning is governed by the interaction
between conceptual modules and other functional modules. A
recurrent connectionist model is developed in which some
inputs are attracted faster than others by an attractor,
where convergence times can beinterpreted as decision
latencies. The learning rule proposed is extracted from
psychological experiments. The rule has the property that
that whena context becomes more familiar, the associations
between the concepts of the context spontaneously evolve
from loose associations to a more taxonomicorganization.
Produkteigenschaften
- Artikelnummer: 9783540576471
- Medium: Buch
- ISBN: 978-3-540-57647-1
- Verlag: Springer Berlin Heidelberg
- Erscheinungstermin: 28.01.1994
- Sprache(n): Englisch
- Auflage: 1994
- Serie: Lecture Notes in Artificial Intelligence
- Produktform: Kartoniert, Paperback
- Gewicht: 1130 g
- Seiten: 347
- Format (B x H x T): 155 x 235 x 20 mm
- Ausgabetyp: Kein, Unbekannt