Synthesizing theories of human language with Bayesian program induction

Synthesizing theories of human language with Bayesian program induction

<jats:title>Abstract</jats:title><jats:p>Automated, data-driven construction and evaluation of scientific models and theories is a long-standing challenge in artificial intelligence. We present a framework for algorithmically synthesizing models of a basic part of human language: m...

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Bibliographic Details
Main Authors: Ellis, Kevin, Albright, Adam, Solar-Lezama, Armando, Tenenbaum, Joshua B, O’Donnell, Timothy J
Other Authors: Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Format: Article
Language:English
Published: Springer Science and Business Media LLC 2023
Online Access:https://hdl.handle.net/1721.1/150387

Internet

https://hdl.handle.net/1721.1/150387

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