Lemma (p. 121) — coordinatewise min/max of two core vectors, paired oppositely, are in the core
ProvedAssignmentGame.CoreCorners.core_latticeLet (sellers) and (buyers) be finite sets and . Let and be two payoff vectors in the core, and define, for and ,
Then both
are in the core.
This lattice property is the heart of Theorem 3: taking sellers' minima together with buyers' maxima (or the reverse) never leaves the core.
import Mathlib import Definitions.Def_AssignmentGame_CoreCorners_Game open Finset
namespace AssignmentGame.CoreCorners
/-- Lemma, p. 121: for two core vectors `(u', v')` and `(u'', v'')`, the vectors
`(min u' u'', max v' v'')` and `(max u' u'', min v' v'')` (taken coordinatewise) are in the
core. -/
theorem core_lattice {M N : Type*} [Fintype M] [Fintype N]
(a : M → N → ℝ) (ha : ∀ i j, 0 ≤ a i j)
(u' u'' : M → ℝ) (v' v'' : N → ℝ)
(h' : (u', v') ∈ core a) (h'' : (u'', v'') ∈ core a) :
((fun i => min (u' i) (u'' i)), (fun j => max (v' j) (v'' j))) ∈ core a ∧
((fun i => max (u' i) (u'' i)), (fun j => min (v' j) (v'' j))) ∈ core a := by sorry
end AssignmentGame.CoreCorners
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What the Lean code literally says, in plain math · claude-opus-5-5
This theorem takes arbitrary finite types and , a real matrix with for all , and two pairs and , where and , both lying in .
Here is the set of with both:
and
The worth is the maximum of over partial matchings , meaning no repeated seller and no repeated buyer, with the empty matching allowed.
The theorem asserts that both of these coordinatewise combinations are also in :
In both, the minimum on one side is paired with the maximum on the other.
Degenerate cases. If , both combinations equal that same vector. If or is empty, the core is a single point, so the two given vectors coincide and the claim is immediate.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.