 Numerous results from experimental economics have shown that these strong rationality assumptions do not describe the behavior of real human subjects. Humans are rarely (if ever) the hyperrational agents described by traditional game theory. For example, it is not uncommon for people, in experimental situations, to indicate that they prefer \(A\) to \(B, B\) to \(C\), and \(C\) to \(A\). These “failures of the transitivity of preference” would not occur if people had a well-defined consistent set of preferences. Furthermore, experiments with a class of games known as a “beauty pageant” show, quite dramatically, the failure of common knowledge assumptions typically invoked to solve  games.[8]  Since evolutionary game theory successfully explains the predominance of certain behaviors of insects and animals, where strong rationality assumptions clearly fail, this suggests that rationality is not as central to game theoretic analyses as previously thought. The hope, then, is that evolutionary game theory may meet with greater success in describing and predicting the choices of human subjects, since it is better equipped to handle the appropriate weaker rationality assumptions. Indeed, one of the great strengths of the framework introduced by Sandholm (2010) is that it provides a general method for linking the learning rules used by individuals, at the micro level, with the dynamics describing changes in the population, at the macro level.