title: How active perception and attractor dynamics shape perceptual categorization: a computational model.
abstract: We propose a computational model of perceptual categorization that fuses elements of grounded and sensorimotor theories of cognition with dynamic models of decision-making. We assume that category information consists in anticipated patterns of agent-environment interactions that can be elicited through overt or covert (simulated) eye movements, object manipulation, etc. This information is firstly encoded when category information is acquired, and then re-enacted during perceptual categorization. The perceptual categorization consists in a dynamic competition between attractors that encode the sensorimotor patterns typical of each category; action prediction success counts as "evidence" for a given category and contributes to falling into the corresponding attractor. The evidence accumulation process is guided by an active perception loop, and the active exploration of objects (e.g., visual exploration) aims at eliciting expected sensorimotor patterns that count as evidence for the object category. We present a computational model incorporating these elements and describing action prediction, active perception, and attractor dynamics as key elements of perceptual categorizations. We test the model in three simulated perceptual categorization tasks, and we discuss its relevance for grounded and sensorimotor theories of cognition.
authors.affiliation: School of Computer Science, Adaptive Systems Research Group University of Hertfordshire, Collage Lane Campus, College Ln, Hatfield, Hertfordshire AL10 9AB, United Kingdom. Electronic address: nicola.catenacci@imtlucca.it.
authors.forename: Nicola
authors.initials: N
authors.lastname: Catenacci Volpi
authors.affiliation: Clermont University, Blaise Pascal University, Pascal Institute, BP 10448, F-63000 Clermont-Ferrand, France; CNRS, UMR 6602, Pascal Institute, F-63171 Aubiere, France. Electronic address: j-charles.quinton@univ-bpclermont.fr.
authors.forename: Jean Charles
authors.initials: JC
authors.lastname: Quinton
authors.affiliation: Istituto di Scienze e Tecnologie della Cognizione - CNR, Via S. Martino della Battaglia, 44 - 00185 Rome, Italy. Electronic address: giovanni.pezzulo@cnr.it.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Pezzulo
mesh_terms: D003071:Cognition; D003657:Decision Making; D006801:Humans; D007858:Learning; D008959:Models, Neurological; D010465:Perception
keywords: Active vision; Dynamic choice; Hopfield networks; Perceptual categorization; Prediction