In Backpropagation we moved smoothly from one hypothesis
to a nearby one. In GA search we can take longer jumps and
maintain a population of hypotheses.
Q: How do we characterize the evolution of a population?
A Schema is a string containing 0, 1, or *. The
* means “don't care.” e.g.
Schema: 10**0*
Instances: 101101, 100100, ...
We can then characterize the population by the number of
instances representing each possible schema.
$m(s,t)$ = number of instances of schema $s$ in population at time $t$.