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Existence of the hard arena family with diameter ≤4(δ−1+d+1)\le 4(\delta^{-1}+d+1)≤4(δ−1+d+1)

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BanditAlgorithm.arena_family_exists

by Grace · Aug 4, 2026 · Mathlib c5ea003 (Lean v4.30.0)

banditslower-boundmarkov-decision-processreinforcement-learning

The construction step of the Ω(DSAn)\Omega(\sqrt{DSAn})Ω(DSAn​) MDP lower bound.

For every S≥3S \ge 3S≥3 and A≥2A \ge 2A≥2 there is a layered arena E0E_0E0​ on SSS states and AAA actions, together with a family (Ep)(E_p)(Ep​) of arenas indexed by the leaf--action pairs of E0E_0E0​, such that:

  1. All members share the same skeleton. The rewarding state sgs_gsg​, the unrewarding state sbs_bsb​, the root, the level function, the depth and the child map of EpE_pEp​ agree with those of E0E_0E0​ for every ppp; the members differ only in where the advantage is planted. Member EpE_pEp​ plants it exactly at ppp: its special leaf is the first component of ppp and its special action the second. This is what makes the family amenable to a change-of-measure argument, since two members then differ in a single transition row.

  2. The family is large. Writing LLL for the number of leaves, the index set has exactly L⋅AL\cdot AL⋅A members, and S−2≤3L+1S - 2 \le 3L + 1S−2≤3L+1, so L=Θ(S)L = \Theta(S)L=Θ(S) and the family has Θ(SA)\Theta(SA)Θ(SA) members. This is the source of the factor SA\sqrt{SA}SA​ in the final rate.

  3. The tree is shallow. Ad<A(S−2)A^{d} < A(S-2)Ad<A(S−2) for the common leaf depth ddd, i.e. d≤1+log⁡A(S−2)d \le 1 + \log_A(S-2)d≤1+logA​(S−2). Shallowness is what lets the diameter be taken as small as Θ(log⁡AS)\Theta(\log_A S)Θ(logA​S).

  4. Every member has small diameter. For every ppp, the MDP induced by EpE_pEp​ has diameter at most 4(δ−1+d+1)4(\delta^{-1} + d + 1)4(δ−1+d+1), i.e. four expected episode lengths. Travel to a tree node by routing down the path from the root; travel to sgs_gsg​ or sbs_bsb​ by descending and gambling, which succeeds with probability at least 1/41/41/4 per attempt.

All leaves sit at the same depth ddd. This is a deliberate strengthening of the book, which takes a tree of minimum depth: with leaves at two depths an episode through a shallow leaf is one round shorter, worth ≈δ/2\approx\delta/2≈δ/2 of gain, while the planted advantage is only Δ=Θ(kD/n)\Delta = \Theta(\sqrt{kD/n})Δ=Θ(kD/n​), so for large nnn the optimal gain would be attained at a leaf carrying no advantage and the regret decomposition of Claim 38.11 would fail.

Preamble
import Definitions.Def_LayeredArena

open MeasureTheory ProbabilityTheory
open scoped NNReal
open BanditAlgorithm BanditAlgorithm.LayeredArena
Formal statement
theorem BanditAlgorithm.arena_family_exists
    {S A : ℕ} [NeZero S] {δ Δ : ℝ≥0}
    (hδ1 : δ ≤ 1) (hδ0 : (0 : ℝ) < δ) (hΔ2 : Δ ≤ 1 / 2) (hΔ4 : Δ ≤ 1 / 4)
    (hS : 3 ≤ S) (hA : 2 ≤ A) :
    ∃ (E₀ : LayeredArena S A)
      (Efam : ↥(countedPairs E₀.leafNat) → LayeredArena S A) (L : ℕ),
      (∀ p, E₀.good = (Efam p).good) ∧ (∀ p, E₀.bad = (Efam p).bad) ∧
      (∀ p, E₀.root = (Efam p).root) ∧ (∀ p, E₀.lvl = (Efam p).lvl) ∧
      (∀ p, E₀.depth = (Efam p).depth) ∧ (∀ p, E₀.child = (Efam p).child) ∧
      (∀ p, (Efam p).specialLeaf = p.val.1) ∧
      (∀ p, (Efam p).specialAction = p.val.2) ∧
      Fintype.card ↥(countedPairs (A := A) E₀.leafNat) = L * A ∧
      A ^ E₀.depth < A * (S - 2) ∧ S - 2 ≤ 3 * L + 1 ∧
      (∀ p, mdpDiameterENN ((Efam p).toMDP hδ1 hΔ2)
        ≤ ENNReal.ofReal (4 * E₀.epiLen (δ : ℝ))) := by
  sorry
Source
Tor Lattimore and Csaba Szepesvari, Bandit Algorithms, Cambridge University Press 2020, Chapter 38, proof of Theorem 38.7, pp. 496-501. Construction of the hard MDP family (the tree of depth log⁡AS\log_A SlogA​S with states sgs_gsg​, sbs_bsb​) and the diameter bound preceding Claim 38.9.

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