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.
Institut des Sciences de l'Evolution, Université de Montpellier, CNRS, IRD, EPHE CC 065 Place Eugène Bataillon 34095 Montpellier cedex 05, France.
Jean-Baptiste
JB
André
CNR, Institute of Cognitive Sciences and Technologies, Laboratory of Autonomous Robots and Artificial Life, Via S. Martino della Battaglia 44, 00185, Roma, Italy.
Stefano
S
Nolfi