AIMC Topic: Choice Behavior

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Using recurrent neural network to estimate irreducible stochasticity in human choice behavior.

eLife Sep 6, 2024
Theoretical computational models are widely used to describe latent cognitive processes. However, these models do not equally explain data across participants, with some individuals showing a bigger predictive gap than others. In the current study, w...
Female Young Adult Adult Neural Networks, Computer Computer Simulation Stochastic Processes Reinforcement, Psychology Choice Behavior Male Decision Making Humans
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Influence of a robotic companion on women's food choices: Evidence from an imaginary task.

Applied psychology. Health and well-being Aug 23, 2024
Previous research has demonstrated the influence of commensal dining between humans on food choices, whereas we conducted two studies to examine how the presence of a robot might influence people's choices between meat-heavy and vegetable-forward mea...
Female Young Adult Adult Humans Vegetables Food Preferences Imagination Male Robotics Choice Behavior
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The consequences of AI training on human decision-making.

Proceedings of the National Academy of Sciences of the United States of America Aug 6, 2024
AI is now an integral part of everyday decision-making, assisting us in both routine and high-stakes choices. These AI models often learn from human behavior, assuming this training data is unbiased. However, we report five studies that show that peo...
Adult Male Choice Behavior Decision Making Artificial Intelligence Female Humans Young Adult
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Autoshaped impulsivity: Some explorations with a neural network model.

Behavioural processes Apr 26, 2024
This study evaluated the effect of delay and magnitude of reinforcement in Pavlovian contingencies, extending the understanding of the phenomenon of autoshaped impulsivity as described in Alcalá's thesis (2017) and Burgos and García-Leal (2015). The ...
Choice Behavior Neural Networks, Computer Animals Impulsive Behavior Conditioning, Classical Reinforcement, Psychology Humans
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Modelling dataset bias in machine-learned theories of economic decision-making.

Nature human behaviour Jan 12, 2024
Normative and descriptive models have long vied to explain and predict human risky choices, such as those between goods or gambles. A recent study reported the discovery of a new, more accurate model of human decision-making by training neural networ...
Humans Neural Networks, Computer Models, Psychological Decision Making Choice Behavior Bias Risk-Taking Datasets as Topic Machine Learning Adult
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Harnessing the flexibility of neural networks to predict dynamic theoretical parameters underlying human choice behavior.

PLoS computational biology Jan 4, 2024
Reinforcement learning (RL) models are used extensively to study human behavior. These rely on normative models of behavior and stress interpretability over predictive capabilities. More recently, neural network models have emerged as a descriptive m...
Humans Reinforcement, Psychology Neural Networks, Computer Choice Behavior Learning Models, Theoretical
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Recurrent networks endowed with structural priors explain suboptimal animal behavior.

Current biology : CB Jan 18, 2023
The strategies found by animals facing a new task are determined both by individual experience and by structural priors evolved to leverage the statistics of natural environments. Rats quickly learn to capitalize on the trial sequence correlations of...
Rats Behavior, Animal Choice Behavior Neural Networks, Computer Learning Animals
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Goals, usefulness and abstraction in value-based choice.

Trends in cognitive sciences Nov 26, 2022
Colombian drug lord Pablo Escobar, while on the run, purportedly burned two million dollars in banknotes to keep his daughter warm. A stark reminder that, in life, circumstances and goals can quickly change, forcing us to reassess and modify our valu...
Goals Choice Behavior Decision Making Artificial Intelligence Brain Mapping Brain Reward
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Flexible control as surrogate reward or dynamic reward maximization.

Cognition Sep 11, 2022
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 ...
Personality Reward Choice Behavior Humans Artificial Intelligence
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Materials In Paintings (MIP): An interdisciplinary dataset for perception, art history, and computer vision.

PloS one Aug 26, 2021
In this paper, we capture and explore the painterly depictions of materials to enable the study of depiction and perception of materials through the artists' eye. We annotated a dataset of 19k paintings with 200k+ bounding boxes from which polygon se...
Statistics as Topic Likelihood Functions Humans Artificial Intelligence Paintings Choice Behavior Time Factors Databases as Topic Perception
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