Architectures of complex learning systems

Abstract

A system which performs a complex combination of behaviours has two superficially independent architectures. One is the functional architecture, which separates the behavioural features of the system into feature modules made up of groups of similar behaviours, and defines the interactions between features. The other is the system architecture (alternatively called the physical or information process architecture) which separates the physical information handling resources of the system into modules that perform different types of information processes, each module optimized to perform a different type of process. Any one feature module will employ information processes performed by many or all resource modules. Many different functional architectures are possible, but the need to limit the resources supporting large numbers of different behaviours tends to constrain the form of the system architecture. In the limiting case as the ratio of the number of behaviours learned to the available resources becomes very large, the system architecture is constrained into a very specific form. In the case of a complex learning system this form is called the recommendation architecture. Because there are natural selection advantages for species that require fewer neural resources to learn a given set of behaviours, there is a tendency for the recommendation architecture form to appear in biological brains including human, mammal and avian brains. A system designed to perform a complex combination of behaviours will be much more effective if designed within this form.