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Simple Search
Hits 1 – 3 of 3
1
Leveraging Recursive Processing for Neural-Symbolic Affect-Target Associations ...
Sutherland, A.
;
Magg, S.
;
Wermter, S.
. - : arXiv, 2021
BASE
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2
Toward a self-organizing pre-symbolic neural model representing sensorimotor primitives.
Zhong, J
;
Cangelosi, A
;
Wermter, S
. - : Switzerland, 2014
Abstract:
The acquisition of symbolic and linguistic representations of sensorimotor behavior is a cognitive process performed by an agent when it is executing and/or observing own and others' actions. According to Piaget's theory of cognitive development, these representations develop during the sensorimotor stage and the pre-operational stage. We propose a model that relates the conceptualization of the higher-level information from visual stimuli to the development of ventral/dorsal visual streams. This model employs neural network architecture incorporating a predictive sensory module based on an RNNPB (Recurrent Neural Network with Parametric Biases) and a horizontal product model. We exemplify this model through a robot passively observing an object to learn its features and movements. During the learning process of observing sensorimotor primitives, i.e., observing a set of trajectories of arm movements and its oriented object features, the pre-symbolic representation is self-organized in the parametric units. These representational units act as bifurcation parameters, guiding the robot to recognize and predict various learned sensorimotor primitives. The pre-symbolic representation also accounts for the learning of sensorimotor primitives in a latent learning context.
Keyword:
horizontal product
;
parametric biases
;
pre-symbolic communication
;
recurrent neural networks
;
sensorimotor integration
URL:
https://doi.org/10.3389/fnbeh.2014.00022
http://hdl.handle.net/10026.1/3602
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3
Noun phrase analysis with connectionist networks
Wermter, S.
;
Lehnert, W.G.
In:
Connectionist approaches to natural language processing
(Hove [etc.], 1992), P. 75-96
MPI für Psycholinguistik
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