Moderate Environmental Variation Across Generations Promotes the Evolution of Robust Solutions

Previous evolutionary studies demonstrated how robust solutions can be obtained by evaluating agents multiple times in variable environmental conditions. Here we demonstrate how agents evolved in environments that vary across generations outperform agents evolved in environments that remain fixed. Moreover, we demonstrate that best performance is obtained when the environment varies at a moderate rate across generations, that is, when the environment does not vary every generation but every N generations. The advantage of exposing evolving agents to environments that vary across generations at a moderate rate is due, at least in part, to the fact that this condition maximizes the retention of changes that alter the behavior of the agents, which in turn facilitates the discovery of better solutions. Finally, we demonstrate that moderate environmental variations are advantageous also from an evolutionary computation perspective, that is, from the perspective of maximizing the performance that can be achieved within a limited computational budget.

Tipo Pubblicazione: 
Articolo
Author or Creator: 
Milano N.
Carvalho J.T.
Nolfi S.
Publisher: 
MIT Press,, Cambridge, MA , Stati Uniti d'America
Source: 
Artificial life 24 (2019): 277–295. doi:10.1162/artl_a_00274
info:cnr-pdr/source/autori:Milano N.; Carvalho J.T.; Nolfi S./titolo:Moderate Environmental Variation Across Generations Promotes the Evolution of Robust Solutions/doi:10.1162/artl_a_00274/rivista:Artificial life/anno:2019/pagina_da:277/pagina_a:295/inter
Date: 
2019
Resource Identifier: 
http://www.cnr.it/prodotto/i/415427
https://dx.doi.org/10.1162/artl_a_00274
info:doi:10.1162/artl_a_00274
http://www.scopus.com/record/display.url?eid=2-s2.0-85062551663&origin=inward
Language: 
Eng
ISTC Author: 
Ritratto di Stefano Nolfi
Real name: