Chapter 13 Local, Global and Glocal Knowledge Representation Co-authored with Matthew Ikle, Joel Pitt and Rui Liu 13.1 Introduction One of the most powerful metaphors we’ve found for understanding minds is to view them as networks — i.e. collections of interrelated, interconnected elements. The view of mind as network is implicit in the patternist philosophy, because every pattern can be viewed as a pattern in something, or a pattern of arrangement of something — thus a pattern is always viewable as a relation between two or more things. A collection of patterns is thus a pattern- network. Knowledge of all kinds may be given network representations; and cognitive processes may be represented as networks also; for instance via representing them as programs, which may be represented as trees or graphs in various standard ways. The emergent patterns arising in an intelligence as it develops may be viewed as a pattern network in themselves; and the relations between an embodied mind and its physical and social environment may be viewed in terms of ecological and social networks. The chapters in this section are concerned with various aspects of networks, as related to intelligence in general and AGI in particular. Most of this material is not specific to CogPrime, and would be relevant to nearly any system aiming at human-level AGI. However, most of it has been developed in the course of work on CogPrime, and has direct relevance to under- standing the intended operation of various aspects of a completed CogPrime system. We begin our excursion into networks, in this chapter, with an issue regarding networks and knowledge representation. One of the biggest decisions to make in designing an AGI system is how the system should represent knowledge. Naturally any advanced AGI system is going to synthesize a lot of its own knowledge representations for handling particular sorts of knowledge — but still, an AGI design typically makes at least some sort of commitment about