282 15 Emergent Networks of Intelligence

282 15 Emergent Networks of Intelligence Fig. 15.2: A typical, though small, subnetwork of WordNet’s hierarchical network. Once elements of hierarchical structure exist via the hierarchical structure of language and physical reality, then a richer and broader hierarchy can be expected to accumulate on top of it, because importance spreading and inference control will implicitly and automatically be guided by the existing hierarchy. That is, in the language of Chaotic Logic [Goe94| and patternist theory, hierarchical structure is an "autopoietic attractor" — once it’s there it will tend to enrich itself and maintain itself. AsymmetricHebbianLinks arranged in a hierarchy will tend to cause importance to spread up or down the hierarchy, which will lead other cognitive processes to look for patterns between Atoms and their hierarchical parents or children, thus potentially building more hierarchical links. Chains of InheritanceLinks pointing up and down the hierarchy will lead PLN to search for more hierarchical links — e.g. most simply, A > B — C where C is above B is above A in the hierarchy, will naturally lead inference to check the viability of A — C by deduction. There is also the possibility to introduce a special DefaultInheritanceLink, as discussed in Chapter 34 of Part 2, but this isn’t actually necessary to obtain the inferential maintenance of a robust hierarchical network. 15.3.2 Associative, Heterarchical Networks Heterarchy is in essence a simpler structure than hierarchy: it simply refers to a network in which nodes are linked to other nodes with which they share important relationships. That is, there should be a tendency that if two nodes are often important in the same contexts or for HOUSE_OVERSIGHT_013198