Strength is a number, associated with a classifier, that keeps some sort of average of the payoffs that the classifier receives. In traditional systems strength is intended as a measure of the classifier's "worth", for two purposes: choosing actions during performance, and selecting classifiers for reproduction under the GA.

The average is usually one that weighs recent payoffs more heavily than earlier ones. Typically,

S(t+1) <-- S(t) + b(P - S(t)),

where b is a "learning rate" something like 0.1, P is the current payoff, and S(t) and S(t+1) are the current and adjusted strengths, respectively.

Notice that the equation tends to push the strength in the direction of the current payoff. In fact, if the payoff is constant for many updates in a row, you can see that the strength converges to it.

What exactly is the "strength" of a classifier"