Toward a self-organizing pre-symbolic neural model representing sensorimotor primitives.
dc.contributor.author | Zhong, J | en |
dc.contributor.author | Cangelosi, A | en |
dc.contributor.author | Wermter, S | en |
dc.date.accessioned | 2015-10-13T15:31:30Z | |
dc.date.accessioned | 2015-10-13T16:08:03Z | |
dc.date.available | 2015-10-13T15:31:30Z | |
dc.date.available | 2015-10-13T16:08:03Z | |
dc.date.issued | 2014 | en |
dc.identifier.issn | 1662-5153 | en |
dc.identifier.uri | http://hdl.handle.net/10026.1/3602 | |
dc.description.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. | en |
dc.format.extent | 22 - ? | en |
dc.language | eng | en |
dc.language.iso | eng | en |
dc.relation.replaces | http://hdl.handle.net/10026.1/3598 | |
dc.relation.replaces | 10026.1/3598 | |
dc.subject | horizontal product | en |
dc.subject | parametric biases | en |
dc.subject | pre-symbolic communication | en |
dc.subject | recurrent neural networks | en |
dc.subject | sensorimotor integration | en |
dc.title | Toward a self-organizing pre-symbolic neural model representing sensorimotor primitives. | en |
dc.type | Journal Article | |
plymouth.author-url | https://www.ncbi.nlm.nih.gov/pubmed/24550798 | en |
plymouth.volume | 8 | en |
plymouth.publication-status | Published online | en |
plymouth.journal | Front Behav Neurosci | en |
dc.identifier.doi | 10.3389/fnbeh.2014.00022 | en |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Research Groups | |
plymouth.organisational-group | /Plymouth/Research Groups/Institute of Health and Community | |
plymouth.organisational-group | /Plymouth/Research Groups/Marine Institute | |
dc.publisher.place | Switzerland | en |
dcterms.dateAccepted | 2014-01-14 | en |
dc.rights.embargoperiod | Not known | en |
rioxxterms.funder | EPSRC | |
rioxxterms.identifier.project | BABEL | |
rioxxterms.versionofrecord | 10.3389/fnbeh.2014.00022 | en |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | en |
rioxxterms.licenseref.startdate | 2014 | en |
rioxxterms.type | Journal Article/Review | en |
plymouth.funder | BABEL::EPSRC | en |
plymouth.oa-location | http://journal.frontiersin.org/article/10.3389/fnbeh.2014.00022/abstract | en |