42 3 A Patternist Philosophy of Mind most AI algorithms suffer from combinatorial explosions: the number of possible elements to be combined in a synthesis or analysis is just too great, and the algorithms are unable to filter through all the possibilities, given the lack of intrinsic constraint that comes along with a “general intelligence” context (as opposed to a narrow-AI problem like chess-playing, where the context is constrained and hence restricts the scope of possible combinations that needs to be considered). In an AGI architecture based on cognitive synergy, the different learning mechanisms must be designed specifically to interact in such a way as to palliate each others’ combinatorial explosions - so that, for instance, each learning mechanism dealing with a certain sort of knowledge, must synergize with learning mechanisms dealing with the other sorts of knowledge, in a way that decreases the severity of combinatorial explosion. One prerequisite for cognitive synergy to work is that each learning mechanism must rec- ognize when it is “stuck,” meaning it’s in a situation where it has inadequate information to make a confident judgment about what steps to take next. Then, when it does recognize that it’s stuck, it may request help from other, complementary cognitive mechanisms. 3.4 The General Structure of Cognitive Dynamics: Analysis and Synthesis We have discussed the need for synergetic interrelation between cognitive processes correspond- ing to different types of memory ... and the general high-level cognitive dynamics that a mind must possess (evolution, autopoiesis). The next step is to dig further into the nature of the cog- nitive processes associated with different memory types and how they give rise to the needed high-level cognitive dynamics. In this section we present a general theory of cognitive processes based on a decomposition of cognitive processes into the two categories of analysis and synthesis, and a general formulation of eac