= Solution
\b[The usual <alpha-beta pruning> inference fails because increasing B's <utility> need not decrease A's <utility>.] A partially explored B-node may have found a child unfavorable to A, but B may prefer an unseen child favorable to A as well. An observed low A-coordinate therefore supplies no upper bound on the A-coordinate ultimately propagated by B.
For a concrete <counterexample>, let a root A-node already have an alternative outcome $(1,0)$. In another B-node, the first explored child yields $(0,1)$. A zero-sum-style cutoff would discard its remaining children because $0<1$. But an unseen child with outcome $(100,2)$ is preferred by B, and makes the complete B-node return $(100,2)$, which A strictly prefers to its incumbent. Such a cutoff changes the answer.
The problem persists even after observing a large B-coordinate: without a known relation between coordinates or useful global <utility> bounds, an unseen pair may have still larger values for both players. Hence there is no generally valid ordinary scalar <alpha-beta pruning> rule for unrestricted <general-sum games>. This does not rule out all <search pruning>: additional bounds, dominance information or a relationship between players' <utilities> can justify specific cutoffs, as in (g).
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