In this paper we demonstrate how differentiated
environmental conditions facilitate the evolution of better solutions in agents evolved for the capacity to solve the double-pole
navigation problem. Moreover, we propose a new evolutionary
algorithm that operates on the basis of multiple environmental
niches characterized by randomly different environmental conditions. The evolving agents are distributed in their own niche but
have the possibility to colonize the other niches. Agents evolved
through this method outperform both agents evolved in fixed
environmental conditions and agents evolved in always varying
environmental conditions.
Publication type:
Contributo in volume
Publisher:
IEEE Computer Society Press, Loa Alamitos [CA], USA
Source:
Proceedings of IEEE Symposium Series on Computational Intelligence, edited by D. Foegel and P. Bonissone (Eds.), pp. 3481–3487. Loa Alamitos [CA]: IEEE Computer Society Press, 2017
info:cnr-pdr/source/autori:Carvalho, Jonata Tyska; Nolfi, Stefano/titolo:Favoring the Evolution of Adaptive Robots Through Environmental Differentiation/titolo_volume:Proceedings of IEEE Symposium Series on Computational Intelligence/curatori_volume:D. Fo
Date:
2017
Resource Identifier:
http://www.cnr.it/prodotto/i/396092
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8280860
Language:
Eng
ISTC Author:
Real name: