pith. sign in

arxiv: cond-mat/0202330 · v1 · submitted 2002-02-20 · ❄️ cond-mat.stat-mech

Optimal design, robustness, and risk aversion

classification ❄️ cond-mat.stat-mech
keywords modelaversioneventshighlyoptimizedpowerriskrobustness
0
0 comments X
read the original abstract

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.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.