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Cognition

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Neural networks, AI, and the goals of modeling.

The Behavioral and brain sciences
Deep neural networks (DNNs) have found many useful applications in recent years. Of particular interest have been those instances where their successes imitate human cognition and many consider artificial intelligences to offer a lens for understandi...

Why psychologists should embrace rather than abandon DNNs.

The Behavioral and brain sciences
Deep neural networks (DNNs) are powerful computational models, which generate complex, high-level representations that were missing in previous models of human cognition. By studying these high-level representations, psychologists can now gain new in...

Clarifying status of DNNs as models of human vision.

The Behavioral and brain sciences
On several key issues we agree with the commentators. Perhaps most importantly, everyone seems to agree that psychology has an important role to play in building better models of human vision, and (most) everyone agrees (including us) that deep neura...

Decentralized policy learning with partial observation and mechanical constraints for multiperson modeling.

Neural networks : the official journal of the International Neural Network Society
Extracting the rules of real-world multi-agent behaviors is a current challenge in various scientific and engineering fields. Biological agents independently have limited observation and mechanical constraints; however, most of the conventional data-...

The effect of different types of cognitive tasks on postural sway fluctuations in older and younger adults: A nonlinear study.

Journal of bodywork and movement therapies
BACKGROUND: There are numerous types of cognitive tasks classified as mental tracking (MT), working memory (WM), reaction time (RT), discrimination and decision-making and verbal fluency (VF). However, limited studies have investigated the effects of...

Psychological factors underlying attitudes toward AI tools.

Nature human behaviour
What are the psychological factors driving attitudes toward artificial intelligence (AI) tools, and how can resistance to AI systems be overcome when they are beneficial? Here we first organize the main sources of resistance into five main categories...

Environmental memory boosts group formation of clueless individuals.

Nature communications
The formation of groups of interacting individuals improves performance and fitness in many decentralised systems, from micro-organisms to social insects, from robotic swarms to artificial intelligence algorithms. Often, group formation and high-leve...

Considering human cognitive architecture in stressful medical prehospital interventions might benefit care providers.

Canadian journal of surgery. Journal canadien de chirurgie
People suffering from critical injuries/illness face marked challenges before transportation to definitive care. Solutions to diagnose and intervene in the prehospital setting are required to improve outcomes. Despite advances in artificial intellige...

Building Human-Like Artificial Agents: A General Cognitive Algorithm for Emulating Human Decision-Making in Dynamic Environments.

Perspectives on psychological science : a journal of the Association for Psychological Science
One of the early goals of artificial intelligence (AI) was to create algorithms that exhibited behavior indistinguishable from human behavior (i.e., human-like behavior). Today, AI has diverged, often aiming to excel in tasks inspired by human capabi...

The Neuroscience of Human and Artificial Intelligence Presence.

Annual review of psychology
Two decades of social neuroscience and neuroeconomics research illustrate the brain mechanisms that are engaged when people consider human beings, often in comparison to considering artificial intelligence (AI) as a nonhuman control. AI as an experim...