Jove
Visualize
Contáctanos

Videos de Conceptos Relacionados

Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

578
Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...
578
Observational Learning01:12

Observational Learning

188
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
188
Associative Learning01:27

Associative Learning

412
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
412
Introduction to Learning01:18

Introduction to Learning

446
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
446
Purposive Learning01:22

Purposive Learning

123
E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
123
Cognitive Learning01:21

Cognitive Learning

249
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
249

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

Diagnostic performance of an artificial intelligence software for diabetic retinopathy organised screening in a pilot study.

Scientific reports·2026
Same author

Correction: A Comprehensive Behavioral Dataset for the Abstraction and Reasoning Corpus.

Scientific data·2025
Same author

A Comprehensive Behavioral Dataset for the Abstraction and Reasoning Corpus.

Scientific data·2025
Same author

Grounded language acquisition through the eyes and ears of a single child.

Science (New York, N.Y.)·2024
Same author

Word meaning in minds and machines.

Psychological review·2021
Same author

Mechanisms for handling nested dependencies in neural-network language models and humans.

Cognition·2021
Same journal

Retraction Note: NSD2 targeting reverses plasticity and drug resistance in prostate cancer.

Nature·2026
Same journal

Enhanced B cell priming induces broadly neutralizing HIV-1 apex antibodies.

Nature·2026
Same journal

Vaccination elicits HIV broadly neutralizing antibodies in primates.

Nature·2026
Same journal

Child online safety needs more than social-media bans.

Nature·2026
Same journal

Ebola preparedness must start with ecosystems and before humans show symptoms.

Nature·2026
Same journal

AI tools can speed up thinking, but evidence still comes from the lab bench.

Nature·2026
Ver todos los artículos relacionados
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Video Experimental Relacionado

Updated: Jul 12, 2025

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.0K

Generalización sistemática similar a la humana a través de una red neuronal de metaaprendizaje

Brenden M Lake1, Marco Baroni2,3

  • 1Department of Psychology and Center for Data Science, New York University, New York, NY, USA. brenden@nyu.edu.

Nature
|October 25, 2023
PubMed
Resumen
Este resumen es generado por máquina.

Las redes neuronales pueden lograr una sistematización similar a la humana en el lenguaje y el pensamiento optimizando sus habilidades compositivas. El enfoque de metaaprendizaje para la composicionalidad (MLC) permite a las redes generalizar de manera flexible, abordando un desafío de larga data en la inteligencia artificial.

Más Videos Relacionados

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.1K
A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents
09:13

A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents

Published on: May 3, 2012

14.4K

Videos de Experimentos Relacionados

Last Updated: Jul 12, 2025

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.0K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.1K
A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents
09:13

A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents

Published on: May 3, 2012

14.4K

Área de la Ciencia:

  • Ciencias cognitivas
  • Inteligencia artificial
  • Lingüística computacional

Sus antecedentes:

  • La cognición humana se basa en la composicionalidad sistemática, lo que permite nuevas combinaciones de elementos conocidos.
  • El desafío de Fodor y Pylyshyn postula que las redes neuronales artificiales carecen de esta sistematicidad, lo que limita su viabilidad como modelos de la mente.
  • A pesar de los avances, lograr una generalización sistemática en las redes neuronales sigue siendo un desafío persistente.

Objetivo del estudio:

  • Para demostrar que las redes neuronales pueden lograr una sistematización similar a la humana.
  • Introducir y evaluar el enfoque de metaaprendizaje para la composicionalidad (MLC).
  • Para comparar las capacidades de generalización de MLC con otros modelos y el rendimiento humano.

Principales métodos:

  • Desarrolló el enfoque de metaaprendizaje para la composicionalidad (MLC), guiando la capacitación de redes neuronales con diversas tareas de composición.
  • Realizó experimentos de comportamiento humano utilizando un paradigma de aprendizaje de instrucciones.
  • Evaluó siete modelos diferentes, incluidos MLC, modelos simbólicos probabilísticos y redes neuronales estándar, en puntos de referencia de generalización sistemática.

Principales resultados:

  • MLC logró con éxito tanto la sistematicidad como la flexibilidad, superando los modelos simbólicos rígidos y las redes neuronales no sistemáticas.
  • MLC demostró capacidades de generalización similares a las humanas en comparaciones directas.
  • MLC mejoró significativamente las habilidades de composición de los sistemas de aprendizaje automático en varios puntos de referencia.

Conclusiones:

  • La optimización de las redes neuronales para las habilidades de composición permite una generalización sistemática similar a la humana.
  • El enfoque MLC proporciona un método viable para desarrollar una inteligencia artificial más capaz y similar a la humana.
  • Esta investigación cierra la brecha entre las redes neuronales artificiales y la naturaleza sistemática del pensamiento y el lenguaje humanos.