AIMC Topic: Reward

Clear Filters Showing 111 to 120 of 121 articles

Confidence-Controlled Hebbian Learning Efficiently Extracts Category Membership From Stimuli Encoded in View of a Categorization Task.

Neural computation Dec 15, 2021
In experiments on perceptual decision making, individuals learn a categorization task through trial-and-error protocols. We explore the capacity of a decision-making attractor network to learn a categorization task through reward-based, Hebbian-type ...
Learning Neurons Reward Humans Neural Networks, Computer Algorithms
View on PubMed DOI

Bridging across functional models: The OFC as a value-making neural network.

Behavioral neuroscience Apr 1, 2021
Many functions have been attributed to the orbitofrontal cortex (OFC)-some classical roles, such as signaling the value of action outcomes, being challenged by more recent ones, such as signaling the position of a trial within a task space. In this p...
Neural Networks, Computer Prefrontal Cortex Reward Humans
View on PubMed DOI

Reinforcement Learning: Full Glass or Empty - Depends Who You Ask.

Current biology : CB Apr 6, 2020
An extension of the prediction error theory of dopamine, imported from artificial intelligence, represents the full distribution over future rewards rather than only the average and better explains dopamine responses.
Dopamine Reinforcement, Psychology Artificial Intelligence Learning Reward
View on PubMed DOI

Human-level performance in 3D multiplayer games with population-based reinforcement learning.

Science (New York, N.Y.) May 31, 2019
Reinforcement learning (RL) has shown great success in increasingly complex single-agent environments and two-player turn-based games. However, the real world contains multiple agents, each learning and acting independently to cooperate and compete w...
Reward Video Games Reinforcement, Psychology Machine Learning
View on PubMed DOI

Predicting similarity judgments in intertemporal choice with machine learning.

Psychonomic bulletin & review Apr 1, 2018
Similarity models of intertemporal choice are heuristics that choose based on similarity judgments of the reward amounts and time delays. Yet, we do not know how these judgments are made. Here, we use machine-learning algorithms to assess what factor...
Algorithms Female Aged Humans Machine Learning Middle Aged Time Factors Decision Making Young Adult Adult Male Judgment Choice Behavior Reaction Time Reward
View on PubMed DOI

Welcome to the Cyborg Olympics.

Nature Aug 4, 2016
Diffusion of Innovation Motivation Exoskeleton Device Man-Machine Systems Competitive Behavior Electric Stimulation Therapy Prostheses and Implants Reward Activities of Daily Living Robotics Switzerland Humans Algorithms Persons with Disabilities
View on PubMed DOI

Can a video game company tame toxic behaviour?

Nature Mar 31, 2016
Humans Machine Learning Algorithms Internet Cultural Characteristics Peer Influence Punishment Social Behavior Reward Video Games Teaching Reinforcement, Psychology Bullying
View on PubMed DOI

A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex.

The Journal of neuroscience : the official journal of the Society for Neuroscience Sep 16, 2015
UNLABELLED: Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in ...
Visual Cortex Membrane Potentials Animals Neuronal Plasticity Nerve Net Neurons Models, Neurological Reward Synaptic Transmission Neural Networks, Computer Reinforcement, Psychology Computer Simulation Learning
View on PubMed DOI

Reinforcement learning improves behaviour from evaluative feedback.

Nature May 28, 2015
Reinforcement learning is a branch of machine learning concerned with using experience gained through interacting with the world and evaluative feedback to improve a system's ability to make behavioural decisions. It has been called the artificial in...
Markov Chains Monte Carlo Method Empirical Research Time Factors Reward Artificial Intelligence Algorithms Feedback
View on PubMed DOI

Human-level control through deep reinforcement learning.

Nature Feb 26, 2015
The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successf...
Models, Psychological Artificial Intelligence Humans Algorithms Neural Networks, Computer Video Games Reward Reinforcement, Psychology
View on PubMed DOI
Popular Topics
Recent Journals