AI Medical Compendium Journal:
Cognition

Showing 21 to 30 of 45 articles

Flexible control as surrogate reward or dynamic reward maximization.

Cognition
The utility of a given experience, like interacting with a particular friend or tasting a particular food, fluctuates continually according to homeostatic and hedonic principles. Consequently, to maximize reward, an individual must be able to escape ...

Conceptual alignment in a joint picture-naming task performed with a social robot.

Cognition
In this study we investigated whether people conceptually align when performing a language task together with a robot. In a joint picture-naming task, 24 French native speakers took turns with a robot in naming images of objects belonging to fifteen ...

Spontaneous perspective taking toward robots: The unique impact of humanlike appearance.

Cognition
As robots rapidly enter society, how does human social cognition respond to their novel presence? Focusing on one foundational social-cognitive capacity-visual perspective taking-seven studies reveal that people spontaneously adopt a robot's unique p...

Pragmatic inferences in aging and human-robot communication.

Cognition
Despite the increase in research on older adults' communicative behavior, little work has explored patterns of age-related change in pragmatic inferencing and how these patterns are adapted depending on the situation-specific context. In two eye-trac...

A neural network model of the effect of prior experience with regularities on subsequent category learning.

Cognition
Categories are often structured by the similarities of instances within the category defined across dimensions or features. Researchers typically assume that there is a direct, linear relationship between the physical input dimensions across which ca...

When unsupervised training benefits category learning.

Cognition
Humans continuously categorise inputs, but only rarely receive explicit feedback as to whether or not they are correct. This implies that they may be integrating unsupervised information together with their sparse supervised data - a form of semi-sup...

A growth mindset about human minds promotes positive responses to intelligent technology.

Cognition
Perceiving minds in technology agents, for example, robots designed with artificial intelligence (AI), is common and crucial in modern life. However, past studies have revealed that robots with a high level of minds elicit polarized responses. From a...

Learning exact enumeration and approximate estimation in deep neural network models.

Cognition
A system for approximate number discrimination has been shown to arise in at least two types of hierarchical neural network models-a generative Deep Belief Network (DBN) and a Hierarchical Convolutional Neural Network (HCNN) trained to classify natur...

Finding event structure in time: What recurrent neural networks can tell us about event structure in mind.

Cognition
Under a theory of event representations that defines events as dynamic changes in objects across both time and space, as in the proposal of Intersecting Object Histories (Altmann & Ekves, 2019), the encoding of changes in state is a fundamental first...

Seeing through disguise: Getting to know you with a deep convolutional neural network.

Cognition
People use disguise to look unlike themselves (evasion) or to look like someone else (impersonation). Evasion disguise challenges human ability to see an identity across variable images; Impersonation challenges human ability to tell people apart. Pe...