  Extensive cooperation among unrelated individuals is unique to humans, who
often sacrifice personal benefits for the common good and work together to
achieve what they are unable to execute alone. The evolutionary success of our
species is indeed due, to a large degree, to our unparalleled other-regarding
abilities. Yet, a comprehensive understanding of human cooperation remains a
formidable challenge. Recent research in social science indicates that it is
important to focus on the collective behavior that emerges as the result of the
interactions among individuals, groups, and even societies. Non-equilibrium
statistical physics, in particular Monte Carlo methods and the theory of
collective behavior of interacting particles near phase transition points, has
proven to be very valuable for understanding counterintuitive evolutionary
outcomes. By studying models of human cooperation as classical spin models, a
physicist can draw on familiar settings from statistical physics. However,
unlike pairwise interactions among particles that typically govern solid-state
physics systems, interactions among humans often involve group interactions,
and they also involve a larger number of possible states even for the most
simplified description of reality. The complexity of solutions therefore often
surpasses that observed in physical systems. Here we review experimental and
theoretical research that advances our understanding of human cooperation,
focusing on spatial pattern formation, on the spatiotemporal dynamics of
observed solutions, and on self-organization that may either promote or hinder
socially favorable states.
