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Lemma 4.26 (Lemma 4.29) — expected payoffs are Lipschitz in the opponents' strategies

Proved
DGPNash.WellSupported.lemma4_26_payoff_diff

by mikedeng1 · Oct 4, 2026 · Mathlib 0df444a (Lean v4.33.1)

approximate-equilibriumgame-theorynash-equilibriump2o-batch-pfp1ap2o-gran-per-chapterp2o-plan-paperp2o-v1

Let xxx and yyy be two mixed profiles of a game in normal form with r≥2r\ge2r≥2 players and nonnegative payoffs usp≥0u^p_s\ge0usp​≥0. For a profile s∈S−ps\in S_{-p}s∈S−p​ of the players other than ppp write xs=∏q≠pxsqqx_s=\prod_{q\ne p}x^q_{s_q}xs​=∏q=p​xsq​q​ and ys=∏q≠pysqqy_s=\prod_{q\ne p}y^q_{s_q}ys​=∏q=p​ysq​q​. Then for every player ppp and every pure strategy j∈Spj\in S_pj∈Sp​,

∣∑s∈S−pujsp xs−∑s∈S−pujsp ys∣ ≤ max⁡s∈S−p{ujsp}∑q≠p∑i∈Sq∣xiq−yiq∣.\Bigl|\sum_{s\in S_{-p}}u^p_{js}\,x_s-\sum_{s\in S_{-p}}u^p_{js}\,y_s\Bigr|\ \le\ \max_{s\in S_{-p}}\{u^p_{js}\}\sum_{q\ne p}\sum_{i\in S_q}\bigl|x^q_i-y^q_i\bigr| .​s∈S−p​∑​ujsp​xs​−s∈S−p​∑​ujsp​ys​​ ≤ s∈S−p​max​{ujsp​}q=p∑​i∈Sq​∑​​xiq​−yiq​​.

The expected payoff of a pure strategy thus moves by at most the largest relevant payoff times the total L1L_1L1​ distance between the opponents' mixed strategies. Lemma 4.29 is this inequality for an approximate equilibrium xxx and its trimmed profile x^\hat xx^.

Formalization Note. r≥2r\ge2r≥2 and u≥0u\ge0u≥0 are the standing assumptions of Sec. 2.1; nonnegativity is used by the bound. The maximum over s∈S−ps\in S_{-p}s∈S−p​ is written as a supremum of upu^pup over full profiles whose ppp-th coordinate is set to jjj, which ranges over the same values. That xxx and yyy are mixed profiles is the context of Sec. 4.6 and is stated explicitly. The sum over q≠pq\ne pq=p is over the players other than ppp.

Preamble
import Mathlib
import Definitions.Def_agt_games
import Definitions.Def_DGPNash_WellSupported_Equilibria
Formal statement
namespace DGPNash.WellSupported

open Finset

/-- **Lemma 4.26 / Lemma 4.29** (Daskalakis–Goldberg–Papadimitriou 2009, p. 240 and p. 244): for
two mixed profiles `x, y` of a game with nonnegative payoffs and at least two players, every player
`p` and every `j ∈ S_p`,
`|Σ_{s ∈ S_{-p}} u^p_{js} x_s − Σ_{s ∈ S_{-p}} u^p_{js} y_s|
  ≤ max_{s ∈ S_{-p}} u^p_{js} · Σ_{q ≠ p} Σ_{i ∈ S_q} |x^q_i − y^q_i|`.
The maximum over `s ∈ S_{-p}` is taken over full profiles `s` with the `p`-th coordinate
overwritten by `j`. -/
theorem lemma4_26_payoff_diff {ι : Type*} [Fintype ι] [DecidableEq ι]
    {S : ι → Type*} [∀ i, Fintype (S i)] [∀ i, DecidableEq (S i)]
    (u : ι → (∀ i, S i) → ℝ) (hu : ∀ p s, 0 ≤ u p s) (hr : 2 ≤ Fintype.card ι)
    (x y : ∀ i, S i → ℝ) (hx : AGT.IsMixedProfile x) (hy : AGT.IsMixedProfile y)
    (p : ι) (j : S p) :
    |DGPNash.NashMap.purePayoff u x p j - DGPNash.NashMap.purePayoff u y p j| ≤
      (⨆ s : (∀ i, S i), u p (Function.update s p j)) *
        ∑ q ∈ Finset.univ.erase p, ∑ i : S q, |x q i - y q i| := by sorry

end DGPNash.WellSupported
Source
Daskalakis, Goldberg & Papadimitriou, The Complexity of Computing a Nash Equilibrium, SIAM J. Comput. 39(1):195–259 (2009), p. 240, Sec. 4.6, Lemma 4.26; instantiated as Lemma 4.29, p. 244, Sec. 4.7
Human review
  • Endorsed by Shuze Chen · Oct 5, 2026

    Confirmed by the moderator at approval.

  • Endorsed by mikedeng1 · Oct 5, 2026

    Confirmed by the mission captain (proposal self-audit).

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