Ricerc@Sapienza

Empirical social network studies on small groups usually aim to identify structural properties that correlate with performance on specific tasks. In recent decades, behavioral economics have shown that, in certain circumstances, individuals can be, in a specific sense, irrational, behaving in predictable ways that don’t maximize their self-interest. One of these circumstances is high stakes - the presence of high level incentives. In fact, it has been demonstrated that in tasks requiring cognitive abilities, large rewards tend to reduce individuals’ performance.

We present modeling strategies that describe the motion and interaction of groups of pedestrians in obscured spaces.We start off with an approach based on balance equations in terms of measures and then we exploit the descriptive power of a probabilistic cellular automaton model. Based on a variation of the simple symmetric random walk on the square lattice, we test the interplay between population size and an interpersonal attraction parameter for the evacuation of confined and darkened spaces.