OpenAI gives an adaptive-anchor and weighted-tree proof that every nonexpansive selfmap of a nonempty closed bounded convex subset of a real reflexive Banach space has a fixed point in the given norm; the manuscript also derives the commuting-family retract corollary from Bruck’s theorem.
OpenAI gives an adaptive-anchor and weighted-tree proof that every nonexpansive selfmap of a nonempty closed bounded convex subset of a real reflexive Banach space has a fixed point in the given norm; the manuscript also derives the commuting-family retract corollary from Bruck’s theorem.
OpenAI gives an adaptive-anchor and weighted-tree proof that every nonexpansive selfmap of a nonempty closed bounded convex subset of a real reflexive Banach space has a fixed point in the given norm; the manuscript also derives the commuting-family retract corollary from Bruck’s theorem.
If correct, supplies a different proof mechanism for the general original-norm theorem amid the unresolved status reported in later literature.
Can an adaptive weighted-tree argument prove the nonexpansive fixed-point property for every real reflexive Banach space in its original norm?
Publication dates and editorial changes.
OpenAI reports an independent proof for reflexive nonexpansive fixed points
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