  Conflict destabilizes social interactions and impedes cooperation at multiple
scales of biological organization. Of fundamental interest are the causes of
turbulent periods of conflict. We analyze conflict dynamics in a monkey society
model system. We develop a technique, Inductive Game Theory, to extract
directly from time-series data the decision-making strategies used by
individuals and groups. This technique uses Monte Carlo simulation to test
alternative causal models of conflict dynamics. We find individuals base their
decision to fight on memory of social factors, not on short timescale
ecological resource competition. Furthermore, the social assessments on which
these decisions are based are triadic (self in relation to another pair of
individuals), not pairwise. We show that this triadic decision making causes
long conflict cascades and that there is a high population cost of the large
fights associated with these cascades. These results suggest that individual
agency has been over-emphasized in the social evolution of complex aggregates,
and that pair-wise formalisms are inadequate. An appreciation of the empirical
foundations of the collective dynamics of conflict is a crucial step towards
its effective management.
