We show how a comprehensive solution to the endogenous qualification problem helps simplify the exogenous qualification problem — the problem of reconciling conflicts between predictions about what should be true at particular times and actual observations.
In particular, we identify the endogenous qualification problem as the problem of properly accounting for highly distributed, and potentially conflicting, causal knowledge when reasoning about the effects of actions.
Definition 11 The Mangasarian-Fromovitz constraint qualification (MFCQ) of the problem (4.7) is said to hold at x ¯ if: (1) the set { D h i ( x ¯ ), i ∈ I } is linearly independent and (2) there exists a ϖ ∈ R n such that for all i ∈ I : D h i ( x ¯ ) ϖ = 0, for all y ¯ ∈ Y 0 ( x ¯ ) : D x L ( x ¯, y ¯ ) ( x ¯, y ¯, λ ¯, β ¯, γ ¯, ν ¯ ) ϖ > 0, for all ( λ ¯, β ¯, γ ¯, v ¯ ) ∈ F ( x ¯, y ¯ ).
Intelligent agents in open environments inevitably face the Qualification Problem: The executability of an action can never be predicted with absolute certainty; unexpected circumstances, albeit unlikely, may at any time prevent the successful performance of an action.
In addition, they encountered the qualification problem: the need for a presumption that an action can be successfully performed, once a short list of essential prerequisites have been met.
You could argue formal coding qualifications actually contribute to the problem highlighted by the Next Gen report.
Frankly put, most of these judges do not have the training or qualifications to identify the problems that exist in a lot of these situations.
Teacher qualifications and pay aren't the problem either.
John McCarthy, on the other hand, still blames the qualification problem.
Yet the main theoretical result known today in this context is a negative one: While a solution to the Qualification Problem requires to assume away by default abnormal qualifications of actions, straightforward minimization of abnormality falls prey to the production of anomalous models.
