Evolutionary dynamics of collaborative environments with heterogeneous agents

Abstract

The seminal work of Maynard Prince and Price in 1973 laid the foundations in establishing the concept of evolutionary game stable strategies. It attempts to select strategies which are robust to evolutionary selection pressures. We observe that most of the literature as evolved is concentrated on single objective games. In this work we extend the notion of evolutionary stability to games with vector payoff functions. We illustrate that this notion of Multicriteria evolutionary stability, models a much larger class of interactions in social, economic and biological problems. Particular applications of interest are in autonomic wireless sensor networks and autonomic networked control systems. We present a multi-population replicator dynamics, which models the evolution of agent actions in a network with varying levels of selfishness. We observe that this model clearly demarks the regions of cooperation among these selfish agents. We provide analytical results on the dynamic stability of the replication. This clearly characterizes the aforementioned demarcations.