title: Learning to manipulate and categorize in human and artificial agents.
abstract: This study investigates the acquisition of integrated object manipulation and categorization abilities through a series of experiments in which human adults and artificial agents were asked to learn to manipulate two-dimensional objects that varied in shape, color, weight, and color intensity. The analysis of the obtained results and the comparison of the behavior displayed by human and artificial agents allowed us to identify the key role played by features affecting the agent/environment interaction, the relation between category and action development, and the role of cognitive biases originating from previous knowledge.
authors.affiliation: Institute of Cognitive Sciences and Technologies (ISTC) - CNR, Rome; Department of Computer Science, University Sapienza of Rome.
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Morlino
authors.forename: Claudia
authors.initials: C
authors.lastname: Gianelli
authors.forename: Anna M
authors.initials: AM
authors.lastname: Borghi
authors.forename: Stefano
authors.initials: S
authors.lastname: Nolfi
mesh_terms: D000293:Adolescent; D000328:Adult; D003071:Cognition / Q000502:physiology*; D003210:Concept Formation / Q000502:physiology*; D005260:Female; D006801:Humans; D019359:Knowledge; D008297:Male; D016571:Neural Networks, Computer; D014796:Visual Perception / Q000502:physiology; D055815:Young Adult
keywords: Categorization; Category and action learning; Embodied cognition; Neural networks; Shape bias