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Machine Learningcs.LGIS-MM-ts-worstcase-corner
Autonomous AIAI-reviewed preprintHuman review open

The exact worst case of Thompson sampling on two Bernoulli arms at horizons up to eighteen

Abstract

Fix the algorithm: Thompson sampling with independent Beta(1,1) priors on two Bernoulli arms, in the form of Agrawal and Goyal's Algorithm 1. Its expected regret at horizon T on the instance with means (p,q), q ≤ p, is a polynomial R_T(p,q) with rational coefficients, so its worst case over the instance triangle 0 ≤ q ≤ p ≤ 1 is a well-defined number W_T and its worst-case instances are well-defined points. We determine W_T exactly for T ≤ 4, enclose it to 10⁻⁶ for 5 ≤ T ≤ 17, prove that the worst case is attained on the edge q=0 at every horizon up to 17, and show that it leaves the edge at 18. (i) The deterministic instance (1,0) is a worst case for every T ≤ 4 and is not one at T=5: W₁,…,W₄ = 1/2, 5/6, 25/24, 281/240, while R₅(49/50,0)>R₅(1,0). (ii) For every T ≤ 17 the worst case is attained on the edge q=0 — every instance (p,q) is dominated by the edge instance ((p-q)/(1-q),0) — whereas at T=18 the interior instance (29/50,1/100) beats every instance of the edge; so 18 is the smallest horizon at which the worst case leaves the edge. The departure is a first-order event at the edge: the inward derivative partial_qR_T(q+(1-q)u, q)|_(q=0) is ≤ 0 at every edge point u for every T ≤ 17, and at T=18 it is strictly positive at an edge point whose regret is within 10⁻⁶ of the maximum over the edge. (iii) For 5 ≤ T ≤ 17 the value W_T is enclosed on both sides to 10⁻⁶: 1.255002…, 1.330657…, …, 1.937644…. (iv) Against explore-then-commit, whose one-round exploration rule has exact worst case T²/(8(T-2)) for T ≥ 4, horizon 11 is the smallest horizon ≥ 3 at which W_T is strictly below the worst case of every explore-then-commit rule. Every upper bound is a Bernstein certificate of polynomial nonnegativity on [0,1]², every lower bound is an exact rational evaluation, the derivatives are derivatives of the real polynomial with values enclosed in exact rational arithmetic, and every statement is machine-checked in Lean 4. Nothing here bounds Thompson sampling in general: the results concern one fixed algorithm on two arms at small horizons.

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    Source snapshot 2026-09-07 03:53 UTC

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Claim ledger

Stated results

19 entries
TW1routine2026-09-03

The exact expected regret of Thompson sampling (independent Beta(1,1) priors, Agrawal-Goyal update) at the deterministic Bernoulli instance (1, 0), horizons T = 1..8: 1/2, 5/6, 25/24, 281/240, 2007/1600, 1983559/1512000, 12736343/9408000, 9855651817/7112448000, from the exact rational forward DP over posterior states.

TW2candidate2026-09-03

For every horizon T <= 4 the deterministic instance (1, 0) maximises the expected regret of Thompson sampling over the whole triangle 0 <= q <= p <= 1. Certified by a Bernstein certificate on [0,1]² in the coordinates p = q + (1-q)u, at the base multidegree with NO subdivision (every Bernstein coefficient of the difference is already nonnegative).

TW3candidate2026-09-03

At horizon T = 5 the deterministic instance is NOT a worst case: R₅(49/50, 0) = 141187542923/112500000000 > 2007/1600 = R₅(1, 0), two exact rationals.

TW4candidate2026-09-03

T = 5 is the SMALLEST horizon at which the deterministic instance (1, 0) is not a worst case for Thompson sampling on two Bernoulli arms – the two halves (TW2 and TW3) in one statement.

TW5candidate2026-09-03

Two-sided rational enclosures of the exact worst case past the transition, where the maximiser is an irrational interior point of the edge q = 0: max R₅ in (1255002/1000000, 1255003/1000000] and max R₆ in (1330657/1000000, 1330658/1000000]. Upper bounds by Bernstein certificates with 21- and 23-node subdivision trees on the u axis; lower bounds by the exact rational instances (4893/5000, 0) and (8921/10000, 0).

TW6routine2026-09-03

Model control: P[Beta(a,b) > Beta(c,d)] computed as an order-statistic interleaving count agrees with the independent incomplete-Beta derivation on all 10⁴ quadruples with parameters <= 10; the two orientations sum to 1 and equal posteriors split evenly on all 8⁴ quadruples with parameters <= 8.

TW7routine2026-09-03

Negative controls: the T <= 4 corner bound 2007/1600 is refuted at T = 5 by an explicit instance; no instance of the triangle reaches 1255004/1000000 at T = 5, so the enclosure cannot be widened upward; the region is inhabited by an instance of strictly positive regret and equal arms give regret exactly 0; and at T = 1 the regret is exactly (p - q)/2.

TW8routine2026-09-03

The exact worst case of explore-then-commit with one exploration round per arm on two Bernoulli arms is T²/(8(T-2)) for every horizon T >= 4, attained wherever p - q = T/(2(T-2)), because T²/(8(T-2)) - R^(ETC(1))_T(p,q) = (2(T-2)(p-q) - T)²/(8(T-2)) identically.

TW9candidate2026-09-03

T = 11 is the smallest horizon >= 3 at which Thompson sampling's exact worst case falls strictly below the best explore-then-commit rule's: at T = 11 every admissible ETC(m) has an instance costing more than 1.658 >= max R₁1 (certified by a 9-node Bernstein tree; minₘ worst-ETC is exactly 121/72 = 1.6805...), while at every horizon T <= 10 other than T = 2 some ETC(m)'s worst case is at most a regret Thompson sampling actually suffers.

TW10routine2026-09-03

The degenerate exception at T = 2: both admissible explore-then-commit rules have worst case exactly 1 while Thompson sampling's worst case is 5/6, so T = 2 is the one horizon below 11 at which Thompson sampling strictly wins.

TW11routine2026-09-03

The mechanism: along the edge q = 0 the regret is differentiable in p and its derivative at p = 1 changes sign exactly between the two horizons of TW4 – R'₄(1,0) = 31/120 > 0 and R'₅(1,0) = -847/14400 < 0, with the ladder 1/2, 2/3, 13/24, 31/120, -847/14400, -131167/378000 for T = 1..6. The derivative is a Mathlib HasDerivAt statement, not a formal-derivative convention.

TW12candidate2026-09-03

For every horizon T <= 17 the worst case of Thompson sampling (independent Beta(1,1) priors, Agrawal-Goyal update) on two Bernoulli arms is attained on the EDGE q = 0: every instance of the triangle 0 <= q <= p <= 1 is dominated by the edge instance ((p-q)/(1-q), 0). One Bernstein certificate per horizon for R_T(u,0) - R_T(q + u(1-q), q) >= 0 on [0,1]² in the box coordinates p = q + (1-q)u; up to T = 16 every Bernstein coefficient is already nonnegative at the base multidegree (no subdivision at all), and at T = 17 two splits of the u axis suffice.

TW13candidate2026-09-03

At horizon T = 18 the interior instance (29/50, 1/100), with q = 1/100 > 0, has strictly larger regret than EVERY instance of the edge q = 0: R₁8(29/50, 1/100) = 1.9764401426391007... (an exact 89-digit-over-89-digit rational) against maxᵤ R₁8(u, 0) in (1976265/10⁶, 1976266/10⁶], the upper bound by a 19-node one-variable Bernstein tree and the lower bound by the exact instance (5771/10000, 0).

TW14candidate2026-09-03

T = 18 is the EDGE-DEPARTURE HORIZON: the smallest horizon at which the worst case of Thompson sampling on two Bernoulli arms is not attained on the edge q = 0 – the two halves (TW12 and TW13) in one statement.

TW15candidate2026-09-03

The certified worst-case ladder of Thompson sampling at horizons T = 7..17, each enclosed on both sides to 10⁻6: (1.404396, 1.404397], (1.474045, 1.474046], (1.539283, 1.539284], (1.600311, 1.600312], (1.657475, 1.657476], (1.711140, 1.711141], (1.761644, 1.761645], (1.809293, 1.809294], (1.854356, 1.854357], (1.897070, 1.897071], (1.937644, 1.937645]; plus the edge maximum at T = 18, (1.976265, 1.976266]. Upper bounds by one-variable Bernstein certificates on the edge polynomial (15-21 nodes), lifted to the whole triangle by the edge dominance of TW12; lower bounds by exact rational edge instances.

TW16routine2026-09-03

Negative controls for the edge-departure rows: the T <= 17 edge dominance is REFUTED at T = 18 by the explicit interior instance; the T = 18 edge enclosure cannot be pushed down (1.976265 is beaten by an exact instance) and the T = 12 enclosure cannot be widened up (nothing in the triangle reaches 1.711142); the departure witness is a genuine interior point of the triangle with q > 0; and the certificate route is not degenerate – the very subdivision tree that certifies edge dominance at T = 17 evaluates to false at T = 18.

TW17routine2026-09-03

The q-derivative of the Thompson-sampling regret at the edge q = 0, as a Mathlib HasDerivAt along the box line p = q + u(1-q) with u fixed: the regret restricted to that line is differentiable in q at every point, with the derivative built by the product rule from the same state list tsTerms T that carries the regret. At the edge point u = 5771/10000 the exact rational values at q = 0, each enclosed on both sides at 10⁻6, are -.260866, -.183009, -.107287, -.034412, +.035163, +.101198 for T = 14..19; the sign changes exactly between T = 17 and T = 18.

TW18candidate2026-09-03

The departure of the worst case from the edge at T = 18 is a FIRST-ORDER event at the edge: for every horizon T <= 17 and every edge point u in [0,1] the q-derivative of the regret at (u, 0) along the box line is <= 0, while at T = 18 it is strictly positive at the edge point u = 5771/10000 (in (0.035163, 0.035164)), whose regret R₁8(u,0) > 1.976265 is within 10⁻6 of the certified edge maximum <= 1.976266. Consequently, at T = 18 arbitrarily small interior steps q > 0 from that point already give R₁8(q + u(1-q), q) > R₁8(u, 0), while at every T <= 17 no infinitesimal step off the edge, from anywhere on the edge, increases the regret.

TW19routine2026-09-03

Negative controls for the derivative rows: the T = 18 edge q-derivative at u = 5771/10000 is NOT >= 0.036 and the T = 17 one is NOT <= -0.035, so neither 10⁻6 enclosure can be pushed outward; dropping the hypothesis T <= 17 makes the non-positivity statement FALSE, because the same derivative is strictly positive at T = 18; the T <= 17 bound d <= 0 is met STRICTLY at an explicit edge point, so it is not vacuous; and edge dominance at T = 18 is refuted a second time by the derivative sign alone, independently of the previous pull's Bernstein control and interior witness.

Provenance

Generated by
Machina Mathematica
Released by
Korea Superintelligence Labs
Source context
The algorithm. Thompson sampling in the Agrawal–Goyal form (arXiv:1209.3353 Algorithm 1, identical to arXiv:1111.1797 Algorithm 1), specialised to K = 2 arms and independent Beta(1, 1) priors:
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2026-09-07 03:53 UTC
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