Tags and the Evolution of Cooperation in Complex Environments

Contents

Cooperation in evolving populations of agents has been explained as arising from kin selection, reciprocity during repeated interactions, and indirect reciprocity through agent reputations. All of these mechanisms require significant agent capabilities, but recent research using computational models has shown that arbitrary markers called "tags" can be used to achieve significant levels of cooperation even in the absence of memory, repeated interactions or knowledge of kin. This is important because it helps to explain the evolution of cooperation in organisms with limited cognitive capabilities, and also because it may help us to engineer cooperative behaviors in multi-agent systems. The computational models used in previous studies, however, have typically been constrained such that cooperation is the only viable strategy for gaining an evolutionary advantage. Here we show that tag-mediated recognition can lead to significant levels of cooperation in a less constrained artificial life simulation, even when other viable survival strategies exist. The results suggest that tags provide a simple yet effective mechanism for promoting the emergence of collective behaviors in evolving agent populations.