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Istituto di scienze e tecnologie della cognizione

Torna all'elenco Contributi in rivista anno 2014

Contributo in rivista

Tipo: Articolo in rivista

Titolo: How active perception and attractor dynamics shape perceptual categorization: A computational model

Anno di pubblicazione: 2014

Formato: Cartaceo

Autori: Volpi, Nicola Catenacci; Quinton, Jean Charles; Pezzulo, Giovanni

Affiliazioni autori: University of Hertfordshire; Blaise Pascal University; Centre National de la Recherche Scientifique (CNRS); Consiglio Nazionale delle Ricerche (CNR)

Autori CNR:

  • GIOVANNI PEZZULO

Lingua: inglese

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. (C) 2014 Elsevier Ltd. All rights reserved.

Pagine da: 1

Pagine a: 16

Pagine totali: 16

Rivista:

Neural networks Pergamon,
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 0893-6080

Numero volume: 60

DOI: 10.1016/j.neunet.2014.06.008

Indicizzato da: ISI Web of Science (WOS) [000347499800001]

Parole chiave:

  • Hopfield networks
  • Perceptual categorization
  • Prediction
  • Active vision
  • Dynamic choice

Strutture CNR:

 
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