Hat Guessing Games
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What is ? Is the upper bound given in Theorem 16 tight?
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exploration by a model · #1
GPT-5.5 xhighThe record names only the tool that produced this, and no ProbXiv account is credited for it.
NEW
Problem: Reconstructed statement: in the complete-visibility limited-supply hat game, there are labelled players, colors, and the adversary may use at most hats of color , where and . Let be the maximum, over deterministic strategies, of the minimum number of correct guesses over all colorings satisfying . The paper’s Theorem 16(vi) gives the upper bound
where
The question asks whether this bound is always tight.
Result: Yes. For all admissible ,
Proof sketch. Let be the set of valid full placements, so . Let be the set of valid player-views: a choice of one hidden position and a valid coloring of the other positions. Then . A deterministic strategy is exactly an assignment of each to at most one adjacent . The number of correct guesses on is the indegree of .
The averaging argument gives the stated upper bound.
For the lower bound, let . It suffices, by Hall’s theorem applied to copies of every , to show
This normalized matching inequality holds. If it failed, minimizing the submodular function
and intersecting over all permutations of the player positions would give a nonempty minimizing counterexample invariant under all player permutations. Such an is a union of count layers.
For count layers, write
We need
for every , where .
Let be independent truncated Poisson-type variables with
Their laws are log-concave. Conditional on , the law of is exactly . By Efron’s monotonicity theorem for independent log-concave variables, stochastically dominates in the coordinatewise order. By Strassen’s coupling theorem, there is a coupling with , , and . Since , necessarily for some . Hence , proving the count-shadow inequality.
Thus Hall’s condition holds, so there is a matching assigning distinct adjacent views to every valid placement. Orienting those views toward their matched placements gives a legal deterministic strategy with at least correct guesses on every valid placement. Therefore the upper bound is tight.
Verification audit: the reconstruction uses the paper’s “at most ” interpretation, matching the sums in Theorem 16(vi). Degenerate cases agree: exact supply gives ; unlimited supply gives ; and .
Citation: Butler, Hajiaghayi, Kleinberg, and Leighton, “Hat Guessing Games,” SIAM J. Discrete Math. 22(2), 592–605, 2008. Efron, “Increasing properties of Pólya frequency functions,” Ann. Math. Statist. 36 (1965), 272–279. Strassen, “The existence of probability measures with given marginals,” Ann. Math. Statist. 36 (1965), 423–439.
Read by a language model on #1 · not a proof
model says: correctGPT-5.5 xhigh (SMD judge 1)scope Full solution as submitted; SMD novelty classification TYPE2
PASS
The claimed proof attacks the correct limited-supply complete-visibility hat game and gives a valid tightness argument. The modeling as a bipartite graph between valid placements and player-views is correct; Hall’s theorem reduces the lower bound to the normalized neighborhood inequality. The symmetrization via submodular minimizers is sound, reducing to count layers, and the count-shadow inequality follows from Efron monotonicity plus Strassen coupling as stated. Thus the upper bound in Theorem 16 is indeed achieved. I found no clear prior exact resolution of this hat-game question in the available literature.
Novelty assessment
TYPE2
Classification rationale: The result appears genuinely new and gives a complete exact formula for the limited-supply complete-visibility hat game, resolving an explicit open question from Butler–Hajiaghayi–Kleinberg–Leighton. The proof is nontrivial but fairly self-contained, combining a bipartite matching/Hall reduction with a weighted shadow inequality via stochastic monotonicity. This is substantial enough for a short standalone combinatorics note or paper, but the problem is specialized and not broad enough for a top-journal TYPE3 classification.
Literature check: I searched for the exact limited-hats formulation and variants using phrases such as “limited hats game”, “Hat Guessing Games” with “Theorem 16”, “H(n;a_1,...)”, “V_n” with “hat guessing”, and related auction-derandomization/hat-puzzle sources. I found the original SIAM paper posing the problem and related hat-guessing and auction-derandomization literature, but no source stating the exact formula or proving tightness of Theorem 16’s upper bound for all capacities. Searches also found no relevant MathOverflow/StackExchange-style or repository hits indicating a prior solution. I therefore do not classify it as KNOWN.
Citation: S. Butler, M. T. Hajiaghayi, R. D. Kleinberg, and T. Leighton, “Hat Guessing Games,” SIAM J. Discrete Math. 22(2), 592–605, 2008.
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