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Istituto di scienze e tecnologie della cognizione

Torna all'elenco Contributi in rivista anno 2011

Contributo in rivista

Tipo: Articolo in rivista

Titolo: Evolution of a predictive internal model in an embodied and situated agent

Anno di pubblicazione: 2011

Autori: Gigliotta, Onofrio; Pezzulo, Giovanni ; Nolfi, Stefano

Affiliazioni autori: LARAL-ISTC ; GOAL-ISTC

Autori CNR:

  • ONOFRIO GIGLIOTTA
  • STEFANO NOLFI
  • GIOVANNI PEZZULO

Lingua: inglese

Abstract: We show how simulated robots evolved for the ability to display a context-dependent periodic behavior can spontaneously develop an internal model and rely on it to fulfill their task when sensory stimulation is temporarily unavailable. The analysis of some of the best evolved agents indicates that their internal model operates by anticipating sensory stimuli. More precisely, it anticipates functional properties of the next sensory state rather than the exact state that sensors will assume. The characteristics of the states that are anticipated and of the sensorimotor rules that determine how the agents react to the experienced states, however, ensure that they produce very similar behaviour during normal and blind phases in which sensory stimulation is available or is self-generated by the agent, respectively. Agents' internal models also ensure an effective transition during the phases in which agents' internal dynamics is decoupled and re-coupled with the sensorimotor flow. Our results suggest that internal models might have arisen for behavioral reasons and successively exapted for other cognitive functions. Moreover, the obtained results suggest that self-generated internal states should not necessarily match in detail the corresponding sensory states and might rather encode more abstract and motor-oriented information.

Lingua abstract: inglese

Pagine da: 259

Pagine a: 276

Rivista:

Theory in biosciences Springer
Paese di pubblicazione: Germania
Lingua: multilingue
ISSN: 1431-7613

Numero volume: 130

Numero fascicolo: 4

DOI: 10.1007/s12064-011-0128-x

Parole chiave:

  • Internal models
  • Evolutionary robotics
  • Prediction

URL: http://dx.doi.org/10.1007/s12064-011-0128-x

Altre informazioni: ID_PUMA: /cnr.istc/2011-A0-077. - Area di valutazione 09 - Ingegneria industriale e informatica

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