Collective action and group formation are fundamental behaviors among both
organisms cooperating to maximize their fitness, and people forming
socioeconomic organizations. Researchers have extensively explored social
interaction structures via game theory and homophilic linkages, such as in kin
selection and scalar stress, to understand emergent cooperation in complex
systems. However, we still lack a general theory capable of predicting how
agents benefit from heterogeneous preferences, joint information, or skill
complementarities in statistical environments. Here, we derive a general
statistical dynamics for the origin of cooperation based on the management of
resources and pooled information. Specifically, we show how groups that
optimally combine complementary agent knowledge about resources in statistical
environments maximize their growth rate. We show that these advantages are
quantified by the information synergy embedded in the conditional probability
of environmental states given agents' signals, such that groups with greater
diversity of signals maximize their collective information. It follows that,
when there are constraints placed on group formation, agents must intelligently
select with who they cooperate with to maximize the synergy available to their
own signal. Our results show how the general properties of information underlie
the optimal collective formation and dynamics of groups of heterogeneous agents
across social and biological phenomena.Comment: 14 pages, 4 figure