title: Evolution of a predictive internal model in an embodied and situated agent.
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.
authors: Natural and Artificial Cognition Laboratory, University of Naples Federico II, via Porta di Massa 1, 80133, Napoli, Italy. onofrio.gigliotta@istc.cnr.it
authors: Onofrio
authors: O
authors: Gigliotta
authors: Giovanni
authors: G
authors: Pezzulo
authors: Stefano
authors: S
authors: Nolfi
authors: Sefano
authors: S
authors: Nolfi
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