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Reward

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Automatic ship classification for a riverside monitoring system using a cascade of artificial intelligence techniques including penalties and rewards.

ISA transactions
Riverside monitoring systems are used for controlling the passage of ships, counting them to prevent overcrowding in a port, or raising an alarm if the ship is unknown or not safe. This type of control and analysis is commonly carried out by many peo...

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

Neural computation
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 ...

Combining STDP and binary networks for reinforcement learning from images and sparse rewards.

Neural networks : the official journal of the International Neural Network Society
Spiking neural networks (SNNs) aim to replicate energy efficiency, learning speed and temporal processing of biological brains. However, accuracy and learning speed of such networks is still behind reinforcement learning (RL) models based on traditio...

Identifying resting state differences salient for resilience to chronic pain based on machine learning multivariate pattern analysis.

Psychophysiology
Studies have documented behavior differences between more versus less resilient adults with chronic pain (CP), but the presence and nature of underlying neurophysiological differences have received scant attention. In this study, we attempted to iden...

Weak Human Preference Supervision for Deep Reinforcement Learning.

IEEE transactions on neural networks and learning systems
The current reward learning from human preferences could be used to resolve complex reinforcement learning (RL) tasks without access to a reward function by defining a single fixed preference between pairs of trajectory segments. However, the judgmen...

Embodied intelligence via learning and evolution.

Nature communications
The intertwined processes of learning and evolution in complex environmental niches have resulted in a remarkable diversity of morphological forms. Moreover, many aspects of animal intelligence are deeply embodied in these evolved morphologies. Howev...

Learning offline: memory replay in biological and artificial reinforcement learning.

Trends in neurosciences
Learning to act in an environment to maximise rewards is among the brain's key functions. This process has often been conceptualised within the framework of reinforcement learning, which has also gained prominence in machine learning and artificial i...

I, robot: depression plays different roles in human-human and human-robot interactions.

Translational psychiatry
Socially engaging robots have been increasingly applied to alleviate depressive symptoms and to improve the quality of social life among different populations. Seeing that depression negatively influences social reward processing in everyday interact...

Systematic review of Pharmacogenomics Knowledgebase evidence for pharmacogenomic links to the dopamine reward pathway for heroin dependence.

Pharmacogenomics
Genetics play an important role in opioid use disorder (OUD); however, few specific gene variants have been identified. Therefore, there is a need to further understand the pharmacogenomics influences on the pharmacodynamics of opioids. The Pharmacog...