Idea: Graph coloring with finitely many colors and unspillability of the important nodes.
If you’ve ever implemented a compiler for a high level language, you’d recognize this as the register allocation phase. This is to say that, by marking certain variables as "unspillable," we prioritize their importance and ensure that they are always kept in the register. And although there are many ways to do this, the most common way, however, is to use graph coloring, where colors can mean registers or stack locations. My hypothesis is that this concept can also be applied to our own cognition and learning, by creating a knowledge graph of the concepts related to a topic and using graph coloring to keep track of which concepts we already understand and which we still need to work on – A graph of known and unknown concepts related to a problem, and making sure that the confusing parts that are crucial to understanding the problem are never spilled over to the stack, in other words, never left to be buffered(dealt with later).
Note that I am not saying you should completely get rid of confusions and uncertainties at all costs, for they are an inevitable part of the problem solving process. Some reveal themselves earlier, while some later in the process. I am saying you should not surrender to the uncertainties and the confusions. These nodes, I believe, when colored have the capacity to facilitate a smooth transition from known unknown to known known (Caveat: This cannot be and should not be applied to unknown unknowns. It can be very dangerous when applied to unknown unknowns as connections in such a graph can lead to unintentional acceptance/rationalization of buffering).
Additionally, I also have a feeling that this has something to with the idea of excluded middles, it's just that I am not sure how exactly. But I think the greediness of the coloring algorithm has something to do with it. Will update this post if I find anything.