Mapping Part-Whole Hierarchies into Connectionist Networks

Three different ways of mapping part-whole hierarchies into connectionist networks are described. The simplest scheme uses a fixed mapping and is inadequate for most tasks because it fails to share units and connections between different pieces of the part-whole hierarchy. Two alternative schemes are described, each of which involves a different method of time-sharing connections and units. The scheme we finally arrive at suggests that neural networks have two quite different methods for performing inference. Simple "intuitive" inferences can be performed by a single settling of a network without changing the way in which the world is mapped into the network. More complex "rational" inferences involve a sequence of such settlings with mapping changes after each settling.