Evolutionary robotics simulations help explain why reciprocity is rare in nature

The relative rarity of reciprocity in nature, contrary to theoretical predictions that it should be widespread, is currently one of the major puzzles in social evolution theory. Here we use evolutionary robotics to solve this puzzle. We show that models based on game theory are misleading because they neglect the mechanics of behavior. In a series of experiments with simulated robots controlled by artificial neural networks, we find that reciprocity does not evolve, and show that this results from a general constraint that likely also prevents it from evolving in the wild. Reciprocity can evolve if it requires very few mutations, as is usually assumed in evolutionary game theoretic models, but not if, more realistically, it requires the accumulation of many adaptive mutations.

Publication type: 
Articolo
Author or Creator: 
Andre, Jean-Baptiste
Nolfi, Stefano
Publisher: 
Nature Publishing Group, London , Regno Unito
Source: 
Scientific reports (Nature Publishing Group) 6 (2016): 1–7. doi:10.1038/srep32785
info:cnr-pdr/source/autori:Andre, Jean-Baptiste; Nolfi, Stefano/titolo:Evolutionary robotics simulations help explain why reciprocity is rare in nature/doi:10.1038/srep32785/rivista:Scientific reports (Nature Publishing Group)/anno:2016/pagina_da:1/pagina
Date: 
2016
Resource Identifier: 
http://www.cnr.it/prodotto/i/366482
https://dx.doi.org/10.1038/srep32785
info:doi:10.1038/srep32785
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5018820/
Language: 
Eng
ISTC Author: 
Stefano Nolfi's picture
Real name: