Computational challenges in explaining communication: How deep the rabbit hole goes
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Computational challenges in explaining communication: How deep the rabbit hole goes

  • Author(s): van de Braak, Laura D.;
  • Dingemanse, Mark;
  • Toni, Ivan;
  • van Rooij, Iris;
  • Blokpoel, Mark
  • et al.
Abstract

When people are unsure of the intended meaning of a word, they often ask for clarification. One way of doing so-often assumed in models of communication-is to point at a potential target: "Do you mean [points at the rabbit]?'' However, what if the target is unavailable? Then the only recourse is language itself, which seems equivalent to pulling oneself up from a swamp by one's hair. We created two computational models of communication, one able to point and one not. The latter incorporates inference to resolve the meaning of non-pointing signals. Simulations show agents in both models reach perceived understanding equally quickly. While this means agents think they are successfully communicating, non-pointing agents understand each other only at chance level. This shows that state-of-the-art computational explanations have difficulty explaining how people solve the puzzle of underdetermination, and that doing so will require a fundamental leap forward.

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