AI Medical Compendium Journal:
Trends in cognitive sciences

Showing 31 to 40 of 47 articles

Unraveling the Mysteries of Motivation.

Trends in cognitive sciences
Motivation plays a central role in human behavior and cognition but is not well captured by widely used artificial intelligence (AI) and computational modeling frameworks. This Opinion article addresses two central questions regarding the nature of m...

Nonmonotonic Plasticity: How Memory Retrieval Drives Learning.

Trends in cognitive sciences
What are the principles that govern whether neural representations move apart (differentiate) or together (integrate) as a function of learning? According to supervised learning models that are trained to predict outcomes in the world, integration sh...

Holding Robots Responsible: The Elements of Machine Morality.

Trends in cognitive sciences
As robots become more autonomous, people will see them as more responsible for wrongdoing. Moral psychology suggests that judgments of robot responsibility will hinge on perceived situational awareness, intentionality, and free will, plus human liken...

Deep Neural Networks as Scientific Models.

Trends in cognitive sciences
Artificial deep neural networks (DNNs) initially inspired by the brain enable computers to solve cognitive tasks at which humans excel. In the absence of explanations for such cognitive phenomena, in turn cognitive scientists have started using DNNs ...

Theories of Error Back-Propagation in the Brain.

Trends in cognitive sciences
This review article summarises recently proposed theories on how neural circuits in the brain could approximate the error back-propagation algorithm used by artificial neural networks. Computational models implementing these theories achieve learning...

Priors in Animal and Artificial Intelligence: Where Does Learning Begin?

Trends in cognitive sciences
A major goal for the next generation of artificial intelligence (AI) is to build machines that are able to reason and cope with novel tasks, environments, and situations in a manner that approaches the abilities of animals. Evidence from precocial sp...

Face Space Representations in Deep Convolutional Neural Networks.

Trends in cognitive sciences
Inspired by the primate visual system, deep convolutional neural networks (DCNNs) have made impressive progress on the complex problem of recognizing faces across variations of viewpoint, illumination, expression, and appearance. This generalized fac...

Parallel Distributed Processing Theory in the Age of Deep Networks.

Trends in cognitive sciences
Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed f...

Do Intelligent Robots Need Emotion?

Trends in cognitive sciences
What is the place of emotion in intelligent robots? Researchers have advocated the inclusion of some emotion-related components in the information-processing architecture of autonomous agents. It is argued here that emotion needs to be merged with al...

Associative Learning Should Go Deep.

Trends in cognitive sciences
Conditioning, how animals learn to associate two or more events, is one of the most influential paradigms in learning theory. It is nevertheless unclear how current models of associative learning can accommodate complex phenomena without ad hoc repre...