Technical discussion of cognitive synergy in AI architecture

Chapter 8 Cognitive Synergy 8.1 Cognitive Synergy As we have seen, the formal theory of general intelligence, in its current form, doesn’t really tell us much that’s of use for creating real-world AGI systems. It tells us that creating extraor- dinarily powerful general intelligence is almost trivial if one has unrealistically huge amounts of computational resources; and that creating moderately powerful general intelligence using feasible computational resources is all about creating AI algorithms and data structures that (explicitly or implicitly) match the restrictions implied by a certain class of situations, to which the general intelligence is biased. We've also described, in various previous chapters, some non-rigorous, conceptual principles that seem to explain key aspects of feasible general intelligence: the complementary reliance on evolution and autopoiesis, the superposition of hierarchical and heterarchical structures, and so forth. These principles can be considered as broad strategies for achieving general intelligence in certain broad classes of situations. Although, a lot of research needs to be done to figure out nice ways to describe, for instance, in what class of situations evolution is an effective learning strategy, in what class of situations dual hierarchical/heterarchical structure is an effective way to organize memory, etc. In this chapter we'll dig deeper into one of the “general principle of feasible general intel- ligences” briefly alluded to earlier: the cognitive synergy principle, which is both a conceptual hypothesis about the structure of generally intelligent systems in certain classes of environments, and a design principle used to guide the architecting of CogPrime. We will focus here on cognitive synergy specifically in the case of “multi-memory systems,” which we define as intelligent systems (like CogPrime) whose combination of environment, embodiment and motivational systems make it important for them to possess memories that divide into partially but not wholly distinct components corresponding to the categories of: Declarative memory Procedural memory (memory about how to do certain things) Sensory and episodic memory Attentional memory (knowledge about what to pay attention to in what contexts Intentional memory (knowledge about the system’s own goals and subgoals) In Chapter 9 below we present a detailed argument as to how the requirement for a multi- memory underpinning for general intelligence emerges from certain underlying assumptions 143 HOUSE_OVERSIGHT_013059