The Entropy of Lies: Playing Twenty Questions with a Liar

Authors Yuval Dagan, Yuval Filmus, Daniel Kane, Shay Moran

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Yuval Dagan
  • Massachusetts Institute of Technology, Cambridge, MA, USA
Yuval Filmus
  • Technion - Israel Institute of Technology, Haifa, Israel
Daniel Kane
  • University of California San Diego, La, Jolla, CA, USA
Shay Moran
  • Technion - Israel Institute of Technology, Haifa, Israel

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Yuval Dagan, Yuval Filmus, Daniel Kane, and Shay Moran. The Entropy of Lies: Playing Twenty Questions with a Liar. In 12th Innovations in Theoretical Computer Science Conference (ITCS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 185, pp. 1:1-1:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


"Twenty questions" is a guessing game played by two players: Bob thinks of an integer between 1 and n, and Alice’s goal is to recover it using a minimal number of Yes/No questions. Shannon’s entropy has a natural interpretation in this context. It characterizes the average number of questions used by an optimal strategy in the distributional variant of the game: let μ be a distribution over [n], then the average number of questions used by an optimal strategy that recovers x∼ μ is between H(μ) and H(μ)+1. We consider an extension of this game where at most k questions can be answered falsely. We extend the classical result by showing that an optimal strategy uses roughly H(μ) + k H_2(μ) questions, where H_2(μ) = ∑_x μ(x)log log 1/μ(x). This also generalizes a result by Rivest et al. (1980) for the uniform distribution. Moreover, we design near optimal strategies that only use comparison queries of the form "x ≤ c?" for c ∈ [n]. The usage of comparison queries lends itself naturally to the context of sorting, where we derive sorting algorithms in the presence of adversarial noise.

Subject Classification

ACM Subject Classification
  • Theory of computation
  • entropy
  • twenty questions
  • algorithms
  • sorting


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