But they amount to learning and search. And because of the politics of Chomsky's movement, it has always fought the concept of learning tooth and nail in favor of innate knowledge or ready-made models. This is why we talk about language "acquisition" and why we read Chomsky saying that contemporaries who studied learning were facilitating totalitarianism.
It's also worth mentioning that Chomsky has stated that he does not think the brain has evolved.
So however many algorithms there are (and however they are employed to get the vast array of intelligent human actions) many things you have said here are totally anathema to Chomsky's school.
It was pushed too hard, it overextended and only now has any challenge come to it - from the quarter of AI. (Up until a few years ago, fighting it in academic Psychology meant you were OK with killing your career, and anyone less respectable than Norvig would get torn apart - look at what they are saying about Norvig now).
Careful here. There could be one algorithm, but we may not be able to express its parameters in the way we like to for simple models.
These statistical approaches are algorithms. It's the fact that we can't make sense of the parameters that seems to lead people to believe that they don't explain anything.
The fact that we can't categorize all life in an unambiguous way that makes sense to humans doesn't mean that the elegant and simple algorithm of evolution by natural selection is wrong.
Model vs. initial conditions. Knowledge vs. search.