Guardado en:
Detalles Bibliográficos
Autores principales: West, Robert L., Eckler, Spencer, Conway-Smith, Brendan, Turcas, Nico, Tomkins-Flanagan, Eilene, Kelly, Mary Alexandria
Formato: Preprint
Publicado: 2024
Materias:
Acceso en línea:https://arxiv.org/abs/2403.18827
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866916181881913344
author West, Robert L.
Eckler, Spencer
Conway-Smith, Brendan
Turcas, Nico
Tomkins-Flanagan, Eilene
Kelly, Mary Alexandria
author_facet West, Robert L.
Eckler, Spencer
Conway-Smith, Brendan
Turcas, Nico
Tomkins-Flanagan, Eilene
Kelly, Mary Alexandria
contents This article presents a theoretical framework for adapting the Common Model of Cognition to large generative network models within the field of artificial intelligence. This can be accomplished by restructuring modules within the Common Model into shadow production systems that are peripheral to a central production system, which handles higher-level reasoning based on the shadow productions' output. Implementing this novel structure within the Common Model allows for a seamless connection between cognitive architectures and generative neural networks.
format Preprint
id arxiv_https___arxiv_org_abs_2403_18827
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Bridging Generative Networks with the Common Model of Cognition
West, Robert L.
Eckler, Spencer
Conway-Smith, Brendan
Turcas, Nico
Tomkins-Flanagan, Eilene
Kelly, Mary Alexandria
Artificial Intelligence
Machine Learning
Neural and Evolutionary Computing
Neurons and Cognition
This article presents a theoretical framework for adapting the Common Model of Cognition to large generative network models within the field of artificial intelligence. This can be accomplished by restructuring modules within the Common Model into shadow production systems that are peripheral to a central production system, which handles higher-level reasoning based on the shadow productions' output. Implementing this novel structure within the Common Model allows for a seamless connection between cognitive architectures and generative neural networks.
title Bridging Generative Networks with the Common Model of Cognition
topic Artificial Intelligence
Machine Learning
Neural and Evolutionary Computing
Neurons and Cognition
url https://arxiv.org/abs/2403.18827