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Active Iterative Social Inference in Multi-Trial Signaling Games.

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Summary
This summary is machine-generated.

Participants partially succeeded in inferring choice priors in complex learning scenarios. Active task engagement and reasoning transparency significantly improved strategic choices and prior inference accuracy in signaling games.

Keywords:
ambiguityinferencelearning about othersonline experimentspragmaticssequential learningsocial learning

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Area of Science:

  • Cognitive Science
  • Behavioral Economics
  • Game Theory

Background:

  • Human decision-making reveals factors influencing choices.
  • Speakers can infer listeners' choice priors from observed ambiguity resolution.
  • Previous studies show limited strategic construction of ambiguous situations for learning.

Purpose of the Study:

  • Investigate prior inference in complex learning scenarios.
  • Examine information accumulation across trials.
  • Assess the impact of active scenario construction on prior inference.

Main Methods:

  • Signaling games were used to study referential ambiguity.
  • Experiment 1: Assessed evidence accumulation over four trials.
  • Experiment 2: Evaluated active scenario construction and iterative settings.

Main Results:

  • Information integration for prior inference was only partially successful.
  • Integration errors included transitivity failure and recency bias.
  • Full task engagement and reasoning transparency enhanced optimal choices and prior inference.

Conclusions:

  • Complex learning scenarios pose challenges for accurate prior inference.
  • Active participation and transparent reasoning pipelines are crucial for strategic decision-making.
  • Improved inference accuracy and strategic utterance choices result from deeper engagement.