AIMC Topic: Reward

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Implicit Value Updating Explains Transitive Inference Performance: The Betasort Model.

PLoS computational biology Sep 25, 2015
Transitive inference (the ability to infer that B > D given that B > C and C > D) is a widespread characteristic of serial learning, observed in dozens of species. Despite these robust behavioral effects, reinforcement learning models reliant on rewa...
Macaca mulatta Male Models, Neurological Computational Biology Models, Statistical Humans Algorithms Reward Machine Learning Learning Animals
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Watching from a distance: A robotically controlled laser and real-time subject tracking software for the study of conditioned predator/prey-like interactions.

Journal of neuroscience methods Jun 22, 2015
BACKGROUND: The physical distance between predator and prey is a primary determinant of behavior, yet few paradigms exist to study this reliably in rodents.
Models, Biological Reward Lasers Brain-Computer Interfaces Rats, Inbred F344 Predatory Behavior Time Factors Rats Robotics Animals Male Rats, Long-Evans Avoidance Learning Software
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A biological mechanism for Bayesian feature selection: Weight decay and raising the LASSO.

Neural networks : the official journal of the International Neural Network Society Mar 25, 2015
Biological systems are capable of learning that certain stimuli are valuable while ignoring the many that are not, and thus perform feature selection. In machine learning, one effective feature selection approach is the least absolute shrinkage and s...
Machine Learning Algorithms Computer Simulation Humans Normal Distribution Online Systems Models, Neurological Bayes Theorem Reward
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Rethinking exploration-exploitation trade-off in reinforcement learning via cognitive consistency.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
The exploration-exploitation dilemma is one of the fundamental challenges in deep reinforcement learning (RL). Agents must strike a trade-off between making decisions based on current beliefs or gathering more information. Prior work mostly prefers d...
Cognition Decision Making Reward Humans Reinforcement, Psychology Neural Networks, Computer Deep Learning
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HCPI-HRL: Human Causal Perception and Inference-driven Hierarchical Reinforcement Learning.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
The dependency on extensive expert knowledge for defining subgoals in hierarchical reinforcement learning (HRL) restricts the training efficiency and adaptability of HRL agents in complex, dynamic environments. Inspired by human-guided causal discove...
Reward Perception Reinforcement, Psychology Humans Neural Networks, Computer Algorithms
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Episodic Memory-Double Actor-Critic Twin Delayed Deep Deterministic Policy Gradient.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Existing deep reinforcement learning (DRL) algorithms suffer from the problem of low sample efficiency. Episodic memory allows DRL algorithms to remember and use past experiences with high return, thereby improving sample efficiency. However, due to ...
Algorithms Deep Learning Reward Humans Memory, Episodic Reinforcement, Psychology
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Reinforcement learning for automated method development in liquid chromatography: insights in the reward scheme and experimental budget selection.

Journal of chromatography. A May 10, 2025
Chromatographic problem solving, commonly referred to as method development (MD), is hugely complex, given the many operational parameters that must be optimized and their large effect on the elution times of individual sample compounds. Recently, th...
Bayes Theorem Reward Automation Deep Learning Chromatography, Liquid Algorithms Computer Simulation
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Unmasking the Dark Triad: A Data Fusion Machine Learning Approach to Characterize the Neural Bases of Narcissistic, Machiavellian and Psychopathic Traits.

The European journal of neuroscience Jan 1, 2025
The Dark Triad (DT), encompassing narcissism, Machiavellianism and psychopathy traits, poses significant societal challenges. Understanding the neural underpinnings of these traits is crucial for developing effective interventions and preventive stra...
White Matter Nerve Net Antisocial Personality Disorder Reward Gray Matter Machiavellianism Narcissism Brain Female Young Adult Adult Male Magnetic Resonance Imaging Humans Machine Learning
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Dynamic Inverse Reinforcement Learning for Feedback-driven Reward Estimation in Brain Machine Interface Tasks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Reinforcement learning (RL)-based brain machine interfaces (BMIs) provide a promising solution for paralyzed people. Enhancing the decoding performance of RL-based BMIs relies on the design of effective reward signals. Inverse reinforcement learning ...
Reinforcement, Psychology Reward Brain-Computer Interfaces Humans Machine Learning Algorithms Feedback
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An approach to solving optimal control problems of nonlinear systems by introducing detail-reward mechanism in deep reinforcement learning.

Mathematical biosciences and engineering : MBE Jun 23, 2022
In recent years, dynamic programming and reinforcement learning theory have been widely used to solve the nonlinear control system (NCS). Among them, many achievements have been made in the construction of network model and system stability analysis,...
Nonlinear Dynamics Problem Solving Neural Networks, Computer Algorithms Reward
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