This work presents an original algorithmic model of some essential features of psychogenetic theory, as was proposed by J. Piaget. Specifically, we modeled some elements of cognitive structure learning in children from birth to four months of life. We are in fact convinced that the study of well-established cognitive models of human learning can suggest new, interesting approaches to problem so far not satisfactorily solved in the field of machine learning. Further, we discussed the possible parallels between our model and subsymbolic machine learning and neuroscience. The model was implemented and tested in some simple experimental settings, with reference to the task of learning sensorimotor sequences.

V. Maniezzo, Roffilli M. (2007). A Psychogenetic Algorithm For Behavioral Sequence Learning. INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS, 16, 195-217 [10.1142/S021821300700328X].

A Psychogenetic Algorithm For Behavioral Sequence Learning

MANIEZZO, VITTORIO;ROFFILLI, MATTEO
2007

Abstract

This work presents an original algorithmic model of some essential features of psychogenetic theory, as was proposed by J. Piaget. Specifically, we modeled some elements of cognitive structure learning in children from birth to four months of life. We are in fact convinced that the study of well-established cognitive models of human learning can suggest new, interesting approaches to problem so far not satisfactorily solved in the field of machine learning. Further, we discussed the possible parallels between our model and subsymbolic machine learning and neuroscience. The model was implemented and tested in some simple experimental settings, with reference to the task of learning sensorimotor sequences.
2007
V. Maniezzo, Roffilli M. (2007). A Psychogenetic Algorithm For Behavioral Sequence Learning. INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS, 16, 195-217 [10.1142/S021821300700328X].
V. Maniezzo; Roffilli M.
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/45263
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact