The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

by Pedro Domingos

We can get even fancier by allowing rules for intermediate concepts to evolve, and then chaining these rules at performance time. For example, we could evolve the rules If the e-mail contains the word loan then it’s a scam and If the e-mail is a scam then it’s spam. Since a rule’s consequent is no longer always spam, this requires introducing additional bits in rule strings to represent their consequents. Of course, the computer doesn’t literally use the word scam; it just comes up with some arbitrary bit string to represent the concept, but that’s good enough for our purposes. Sets of rules like this, which Holland called classifier systems, are one of the workhorses of the machine-learning tribe he founded: the evolutionaries. Like multilayer perceptrons, classifier systems face the credit-assignment problem—what is the fitness of rules for intermediate concepts?—and Holland devised the so-called bucket brigade algorithm to solve it. Nevertheless, classifier systems are much less widely used than multilayer perceptrons.