We explore some unorthodox models for studying primate societies as self-organized and, hence, nonlinear complex systems. The incentive is that the conventional rationalist-analytic approach often leads to superfluous and contrived explanations. This is due to the habit of seeking separate explanations for each observed phenomenon, the tendency to ascribe social patterns solely to cognitive or genetic qualities of individuals, and the use of a short-sighted logic that yields naive predictions. These practices stem from the desire to produce testable predictions derived from a normative perspective, leading to a disregard of real world properties like nonlinear dynamics, the effects of numerous parallel interactions, and the importance of local spatial configurations. We illustrate how dynamical systems and individualoriented models explicitly include these features by starting from a synthetic perspective. As a result, they generate versatile, and often counterintuitive, insights into primate social behavior. The hypotheses derived in this way are parsimonious in the sense that a multitude of patterns can be traced back to one and the same minimal set of interactive dynamics. This type of model therefore leads to more integrating and comprehensive explanations than the purely function- alistic top-down approaches of cognitive science and neo-Darwinian evolutionary theory. We suggest that building autonomous robots and studying their performance might yield additional understanding of self-organized collective behavior in the real world. As mechanistic implementations of principles discovered in silica, robots form an interesting extension to individual-oriented models because they confront us with important real world conditions and physical constraints that are hard to program or would go otherwise unnoticed. In this chapter we use examples from primatology to tackle problems in the study of (small-scale) human societies. In contrast to the usual rationale, our objective is not to learn about our own kind by regarding monkeys and apes as simplified versions of humans. Instead, we argue that certain features of both human and nonhuman social behavior rest on common principles of selfstructuring and that studying these may shed light on general issues of social organization.
Culling the Herd: Using Real-World Randomized Experiments to Measure Social Bias with Known Costly Goods
