Evolving robots able to self-localize in the environment: The importance of viewing cognition as the result of processes occurring at different time scales

In this paper we address the problem of synthesizing mobile robots able
to solve problems in which they cannot merely react to sensory input, but
have to maintain an internal state as well. More precisely we will show
how autonomous robots synthesized through an evolutionary process can
solve problems that necessarily require an ability to integrate sensory-
motor information over time. By presenting the result of a set of
experiments in which evolving robots are asked to navigate and self-
localize in the environment, we will show that successful results can be
achieved by providing evolving individuals with neural controllers with
neurons that (a) vary their activity at different rates to detect
regularities at different time scales in the sensory-motor flow, and (b)
use thresholded activation functions to detect events extending over
time.

Publication type: 
Articolo
Author or Creator: 
Nolfi S.
Publisher: 
Carfax Publishing,, Abingdon (P.O.Box 25, Abingdon, Oxfordshire OX14 3UE) , Regno Unito
Source: 
Connection science (Print) 3 (2002): 231–244.
info:cnr-pdr/source/autori:Nolfi S./titolo:Evolving robots able to self-localize in the environment: The importance of viewing cognition as the result of processes occurring at different time scales/doi:/rivista:Connection science (Print)/anno:2002/pagina
Date: 
2002
Resource Identifier: 
http://www.cnr.it/prodotto/i/46686
ISTC Author: 
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