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Behavior

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Comparing feedforward and recurrent neural network architectures with human behavior in artificial grammar learning.

Scientific reports
In recent years artificial neural networks achieved performance close to or better than humans in several domains: tasks that were previously human prerogatives, such as language processing, have witnessed remarkable improvements in state of the art ...

Unsupervised manifold learning of collective behavior.

PLoS computational biology
Collective behavior is an emergent property of numerous complex systems, from financial markets to cancer cells to predator-prey ecological systems. Characterizing modes of collective behavior is often done through human observation, training generat...

Behavioral correlates of cortical semantic representations modeled by word vectors.

PLoS computational biology
The quantitative modeling of semantic representations in the brain plays a key role in understanding the neural basis of semantic processing. Previous studies have demonstrated that word vectors, which were originally developed for use in the field o...

Bad machines corrupt good morals.

Nature human behaviour
As machines powered by artificial intelligence (AI) influence humans' behaviour in ways that are both like and unlike the ways humans influence each other, worry emerges about the corrupting power of AI agents. To estimate the empirical validity of t...

Noise-trained deep neural networks effectively predict human vision and its neural responses to challenging images.

PLoS biology
Deep neural networks (DNNs) for object classification have been argued to provide the most promising model of the visual system, accompanied by claims that they have attained or even surpassed human-level performance. Here, we evaluated whether DNNs ...

Spatiotemporal dynamics in spiking recurrent neural networks using modified-full-FORCE on EEG signals.

Scientific reports
Methods on modelling the human brain as a Complex System have increased remarkably in the literature as researchers seek to understand the underlying foundations behind cognition, behaviour, and perception. Computational methods, especially Graph The...

Unpredictable robots elicit responsibility attributions.

The Behavioral and brain sciences
Do people hold robots responsible for their actions? While Clark and Fischer present a useful framework for interpreting social robots, we argue that they fail to account for people's willingness to assign responsibility to robots in certain contexts...

The Inversion Problem: Why Algorithms Should Infer Mental State and Not Just Predict Behavior.

Perspectives on psychological science : a journal of the Association for Psychological Science
More and more machine learning is applied to human behavior. Increasingly these algorithms suffer from a hidden-but serious-problem. It arises because they often predict one thing while hoping for another. Take a recommender system: It predicts click...

A Turing test of whether AI chatbots are behaviorally similar to humans.

Proceedings of the National Academy of Sciences of the United States of America
We administer a Turing test to AI chatbots. We examine how chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairness, risk-aversion, cooperation, etc., as well as how they respond to a ...