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Racionalidad computacional: un paradigma convergente para la inteligencia en cerebros, mentes y máquinas
Samuel J Gershman1, Eric J Horvitz2, Joshua B Tenenbaum3
1Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA. gershman@fas.harvard.edu horvitz@microsoft.com jbt@mit.edu.
Science (New York, N.Y.)
|July 18, 2015
Resumen
La inteligencia artificial (IA), la ciencia cognitiva y la neurociencia se están fusionando, centrándose en la inteligencia computacional. Esta reconvergencia impulsa la innovación en la percepción, la acción y la toma de decisiones bajo incertidumbre.
Área de la Ciencia:
- Investigación interdisciplinaria en la intersección de la inteligencia artificial (IA), la ciencia cognitiva y la neurociencia.
Sus antecedentes:
- Los campos históricamente separados ahora están convergiendo en teorías computacionales compartidas de la inteligencia.
- Esta reconvergencia fomenta la colaboración interdisciplinaria y el intercambio de conocimientos.
Objetivo del estudio:
- Trazar avances en la comprensión de la percepción y la acción bajo incertidumbre a través de la computación.
- Explorar el desarrollo de la racionalidad computacional para la toma de decisiones óptima.
Principales métodos:
- Revisando décadas de progreso en los enfoques computacionales de la inteligencia.
- Examinar las representaciones e inferencias para el razonamiento probabilístico.
- Máquinas de análisis para las compensaciones computacionales (esfuerzo, precisión, puntualidad).
Principales resultados:
- Desarrollo de métodos de inferencia probabilística a gran escala.
- Máquinas que permiten la reflexión sobre las compensaciones computacionales.
- Aplicación de la racionalidad computacional a problemas complejos del mundo real.
Conclusiones:
- La convergencia de la IA, la ciencia cognitiva y la neurociencia ofrece una visión unificada de la inteligencia.
- Los enfoques computacionales proporcionan herramientas poderosas para abordar los desafíos de percepción, acción y toma de decisiones.
- El intercambio entre estos campos tiene un potencial significativo para futuros descubrimientos científicos.
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