318 18 Advanced Self-Modification: A Possible Path to Superhuman AGI only after these have achieved something close to human-level general intelligence (even if not precisely humanlike general intelligence). Another troublesome issue regarding self-modification is that the boundary between "self- modification" and learning is not terribly rigid. In a sense, all learning is selfmodification: if it doesn’t modify the system’s knowledge, it isn’t learning! Particularly, the boundary between "learning of cognitive procedures" and "profound self-modification of cognitive dynamics and structure" isn’t terribly clear. There is a continuum leading from, say, 1. learning to transform a certain kind of sentence into another kind for easier comprehension, or learning to grasp a certain kind of object, to 2. learning a new inference control heuristic, specifically valuable for controlling inference about (say) spatial relationships; or, learning a new Atom type, defined as a non-obvious judiciously chosen combination of existing ones, perhaps to represent a particular kind of frequently-occurring mid-level perceptual knowledge, to 3. learning a new learning algorithm to augment MOSES and hillclimbing as a procedure learning algorithm, to 4, learning a new cognitive architecture in which data and procedure are explicitly identical, and there is just one new active data structure in place of the distinction between AtomSpace and MindAgents Where on this continuum does the "mere learning" end and the "real self-modification" start? In this chapter we consider some mechanisms for "advanced self-modification" that we believe will be useful toward the more complex end of this continuum. These are mechanisms that we strongly suspect are not needed to get a CogPrime system to human-level general intelligence. However, we also suspect that, once a CogPrime system is roughly near human-level general intelligence, it will be able to use these mechanisms to rapidly increase aspects