Definition Convex Combination of Simplex Points
definition formalized

Convex Combination of Simplex Points

The basic vocabulary for blending two mixed strategies. Given $x, y \in \Delta(I)$ and $\alpha \in [0, 1]$, the mixed point

$$ \mathrm{mix}(\alpha; x, y) \;=\; \alpha \cdot x + (1 - \alpha) \cdot y $$

is again a simplex point. This is the substrate for compound lotteries (MSZ Axiom 2.16), the inductive perturbation step in Loomis-style minimax proofs, and any algorithm that interpolates between two distributions (fictitious play, no-regret dynamics, Sion-style continuity arguments).

Statement

For a finite index I, a strictly ordered field 𝕜, and α ∈ [0, 1]:

  • stdSimplex.mix α hα₀ hα₁ x y is the element of stdSimplex 𝕜 I whose i-th coordinate is $\alpha \cdot x_i + (1 - \alpha) \cdot y_i$.
  • Bilinearity of wsum (wsum_mix): for any f : I → 𝕜, $$ \operatorname{wsum}(\mathrm{mix}(\alpha; x, y), f) \;=\; \alpha \cdot \operatorname{wsum}(x, f) + (1 - \alpha) \cdot \operatorname{wsum}(y, f). $$
  • Strict-monotonicity over a convex combination (linear_comb_gt_of_ge_gt, linear_comb_lt_of_le_lt, and their wsum versions wsum_mix_gt_of_ge_gt and wsum_mix_lt_of_le_lt): if one endpoint of the combination satisfies a non-strict bound and the other a strict bound, the combination remains strict for any α < 1.
  • Neighborhood-of-1 existential (mix_gt_of_gt_nbh and dual mix_lt_of_lt_nbh): if c < x, there is an interior t ∈ (0, 1) with c < t · x + (1 - t) · y. The proof appeals to continuity of $s \mapsto s \cdot x + (1 - s) \cdot y$ at $s = 1$.

Hypothesis convention

Hypotheses for α are passed as plain (α : 𝕜) (hα₀ : 0 ≤ α) (hα₁ : α ≤ 1) rather than via a unit-interval subtype, matching Mathlib idioms and avoiding a Core-level subtype declaration that would not pay for itself. The legacy Interval := { t : ℝ // 0 ≤ t ∧ t ≤ 1 } subtype, previously defined in StrategicGame/MinimaxLoomis.lean, has been retired in favor of this convention.

Use

  • EconCSLib.Utility.Lottery: Lottery.mix is a definitional alias of stdSimplex.mix; Lottery.expectedValue_mix is a one-line wrapper around wsum_mix.
  • EconCSLib.StrategicGame.MinimaxLoomis (simplified Loomis induction) and EconCSLib.StrategicGame.Loomis (general-B Loomis): the inductive step "blend the existing optimiser with the optimiser of the smaller restricted game" is the canonical consumer of stdSimplex.mix, wsum_mix, wsum_mix_*_of_*, and mix_*_nbh.

References

  • [MSZ] Maschler, Solan, Zamir, Game Theory, Axiom 2.16 and the surrounding discussion of compound lotteries.
  • [MFoGT] Laraki, Renault, Sorin, Mathematical Foundations of Game Theory, Section 2.5 (Loomis induction).

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