9.3. Embodied Communication 165 The NKC assumption seems commonsensically to hold true for human everyday knowledge, and it has fairly dramatic implications for general intelligence. Suppose we conceive general intelligence as the ability to achieve goals in the environment shared by the communicating agents underlying the Embodied Communication Prior. Then, NKC suggests that the best way to achieve general intelligence according to the Embodied Communication Prior is going to involve ® specialized methods for handling declarative, procedural, sensory and attentional knowledge (due to the naturalness of the isolated knowledge categories) ® specialized methods for handling interactions between different types of knowledge, includ- ing methods focused on the case where one type of knowledge is primary and the others are supporting (the latter due to the naturalness of the interactive knowledge categories) 9.3.0.2 Cognitive Completeness Suppose we conceive an AI system as consisting of a set of learning capabilities, each one characterized by three features: e One or more knowledge types that it is competent to deal with, in the sense of the two key learning problems mentioned above e At least one learning type: either analysis, or synthesis, or both e At least one interaction type, for each (knowledge type, learning type) pair it handles: “isolated” (meaning it deals mainly with that knowledge type in isolation), or “interactive” (meaning it focuses on that knowledge type but in a way that explicitly incorporates other knowledge types into its process), or “fully mixed” (meaning that when it deals with the knowledge type in question, no particular knowledge type tends to dominate the learning process). Then, intuitively, it seems to follow from the ECP with NKC that systems with high efficient general intelligence should have the following properties, which collectively we'll call cognitive completeness: e For each (knowledge type, learning type, interaction