Network Formation by Contagion Averse Agents: Modeling Bounded Rationality with Logit Learning

Economic and convenience benefits of interconnectivity drive current explosive emergence and growth of networked systems. However, as recent catastrophic contagious failures in numerous large scale networked infrastructures demonstrated, these benefits of interconnectivity are inherently associated with various risks, including risk of undesirable contagion. Current research on network formation by contagion risk averse agents, which analyzes Nash or some other game-theoretic equilibrium notion of the corresponding game, suffers from interrelated problems of intractability and oversimplification. We argue that these problems can be alleviated with dynamic view, which assumes logit responses by strategic agents with utilities quantifying multiple competing incentives. While this approach naturally incorporates practically critical assumption of bounded rationality, it also allows for leveraging a vast body of results on network formation, e.g., preferential attachment in growing networks.