An affine function preserves mixtures, so
Therefore
The positive mixture weight preserves the strict sign; the common component cancels. This is the independence axiom for lottery preferences for the affine utility on probability measures.
Indifference means equality of the representing utility values. Since , set
Applying the affine function identity gives , so . This proves mixture solvability of affine preferences. The displayed weight is unique because the two endpoint utilities differ.
First, equality of two values forces equality of the corresponding values: neither strict comparison holds for , and the same is then true for in both directions. Thus for a well-defined strictly increasing function on . Since is a convex set and are affine functions, is a real interval and
If contains , let and . The mixture identity gives for . For , express as a convex combination of and and solve the same identity for ; for , express as a mixture of and . Hence the formula holds on all of , not merely between the chosen anchors. We obtain positive affine uniqueness of affine preference representations:
If is constant, the same comparisons force to be constant; choose and the appropriate . If the probability-measure set is empty, the assertion is vacuous. These degenerate cases do not require distinct anchors.
Define , where is the Dirac measure at . For the full sigma-algebra of subsets of a finite , affineness directly gives .
The statement also holds for an arbitrary sigma-algebra on a finite set. List each atom of a sigma-algebra as and choose . Points in one atom have identical Dirac measures on this sigma-algebra, so is constant on each atom and is measurable. Every probability measure decomposes as , whence
This is the expected utility representation on a finite measurable space. It does not silently assume that each singleton is measurable.

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