  We introduce a minimal agent-based model to qualitatively conceptualize the
allocation of limited wealth among more abundant opportunities. We study the
interplay of power, satisfaction and frustration in distribution,
concentration, and inequality of wealth. Our framework allows us to compare
subjective measures of frustration and satisfaction to collective measures of
fairness in wealth distribution, such as the Lorenz curve and the Gini index.
We find that a completely libertarian, law-of-the-jungle setting, where every
agent can acquire wealth from, or lose wealth to, anybody else invariably leads
to a complete polarization of the distribution of wealth vs. opportunity. The
picture is however dramatically modified when hard constraints are imposed over
agents, and they are limited to share wealth with neighbors on a network. We
then propose an out of equilibrium dynamics {\it of} the networks, based on a
competition between power and frustration in the decision-making of agents that
leads to network coevolution. We show that the ratio of power and frustration
controls different dynamical regimes separated by kinetic transitions and
characterized by drastically different values of the indices of equality. The
interplay of power and frustration leads to the emergence of three
self-organized social classes, lower, middle, and upper class, whose
interactions drive a cyclical regime.
