Many of the pressing challenges facing contemporary society concern sustainability and public health. For example, how can sustainable behaviors—such as reducing individual energy consumption—be encouraged? How can participation in activities that reduce overall healthcare costs—such as compliance with preventive care routines and leading healthy lifestyles—be supported? Common to these challenges is a fundamental question: how can we facilitate cooperative behavior adoption on a large scale?
The conditions for self-governance found in small groups do not apply in large populations. As a result, the question of how cooperation can be facilitated in large populations remains unanswered and is the focus of my work. In this talk, I shall discuss the computational tools needed to engender cooperation in heterogenous populations. The first step towards facilitating cooperative behavior adoption within large heterogeneous populations is to unite similar individuals within the population into small homogenous groups or communities. I shall present our work on discovering homogenous groups and discuss compressed sensing techniques to analyze large scale network changes. I shall briefly touch upon open questions on the social cooperative capacity of a group, and design of signaling schemes to increase cooperation.