  Highly optimized tolerance is a model of optimization in engineered systems,
which gives rise to power-law distributions of failure events in such systems.
The archetypal example is the highly optimized forest fire model. Here we give
an analytic solution for this model which explains the origin of the power
laws. We also generalize the model to incorporate risk aversion, which results
in truncation of the tails of the power law so that the probability of
disastrously large events is dramatically lowered, giving the system more
robustness.
