FROM SELFISHNESS & ALTRUISM TO MACRO-BEHAVIOR

Abstract

The central subject of this paper is the relation between the macro-level of the Society and the micro-level of its individuals. In complex real-life systems, this relationship is not trivial and even the result at the macro-level can be counter-intuitive. One of the first models that highlights this is the Sakoda and Schelling’s model of spatial segregation where a person uses a selfish rule to decide whether or not to leave his current place; on the basis of the ratio of “compatible” agents in the neighborhood of each individual, simulations have shown that tolerant agents group together beyond what their own tolerance imposes. This paper compares the macro-behavior arising from either selfish or altruist micro-motives; for this purpose, we propose agent-based computational models based, respectively, on selfishness, altruism and a mixture of both. Computational simulations show that (i) in a totally altruistic population, a vast majority becomes satisfied as if the agents were themselves selfish and end up spatially segregated; (ii) altruist micro-motives allow to reduce both the micro-macro gap and the segregation phenomenon; (iii) in a mixed population, the macro-effect depends both on the respective weight of each micro-motives and the allocation strategy.