Wikipedia says “an algorithm is an unambiguous specification of how to solve a class of problems.” Asa H, as a non-algorithmic system, does not know how to solve the problem it faces (achieving high vector utility). It discovers specifications for success by acting in and observing the world around it. Such specifications may change over time as the world (and Asa) change. An "algorithm" begins its life with the knowledge it needs, a non-algorithmic system like Asa H begins without such knowledge but slowly discovers it. In the beginning Asa only needs to know enough to get started in its search.
So what is the minimum Asa (or some other AI) needs to begin with so that it can get started learning? That depends upon the world it finds itself in. The idea of a curriculum for Asa has been an attempt to present a sequence of more and more difficult tasks and environments which help Asa to grow. (Much in the way we structure grade school lessons for human children. Protecting them from “the real world” for a while.)
See also my blog of 23 March 2015.
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