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Predicción del razonamiento pragmático en juegos de lenguaje.

Michael C Frank1, Noah D Goodman

  • 1Department of Psychology, Stanford University, Stanford, CA 94305, USA. mcfrank@stanford.edu

Science (New York, N.Y.)
|May 26, 2012
PubMed
Resumen

El lenguaje humano transmite eficientemente información a través del contexto. La inferencia bayesiana y la teoría de la información ofrecen predicciones precisas para el razonamiento pragmático en la comunicación, mejorando los modelos formales.

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Área de la Ciencia:

  • Ciencias Cognitivas Ciencias Cognitivas.
  • La lingüística es la lingüística de las lenguas.
  • La neurociencia computacional es una neurociencia computacional.

Sus antecedentes:

  • El lenguaje humano sobresale en la transferencia de información eficiente y dependiente del contexto.
  • Las teorías existentes de inferencia comunicativa carecen de poder predictivo preciso y cuantitativo para el razonamiento pragmático.

Objetivo del estudio:

  • Desarrollar y probar un modelo cuantitativo de razonamiento pragmático en la comunicación referencial.
  • Evaluar la utilidad de las herramientas teóricas de la información y la inferencia bayesiana en el modelado de la comunicación humana.

Principales métodos:

  • Examinó los juicios humanos en juegos de comunicación referenciales simples.
  • Informatividad del hablante modelado y inferencia bayesiana del oyente para la recuperación del referente.
  • Utilizó los principios teóricos de la información para predecir el razonamiento pragmático.

Principales resultados:

  • El modelo propuesto demostró un ajuste cercano y libre de parámetros a los juicios humanos.
  • La inferencia bayesiana captura efectivamente cómo los oyentes recuperan los referentes previstos.
  • Los principios teóricos de la información predicen con precisión los patrones de razonamiento pragmático.

Conclusiones:

  • La inferencia bayesiana proporciona un marco sólido para la comprensión del razonamiento pragmático en la comunicación humana.
  • Las herramientas teóricas de la información son valiosas para desarrollar modelos precisos y cuantitativos de comunicación.
  • Este enfoque avanza en el modelado formal del lenguaje y la cognición.