AIMC Topic: Reinforcement Machine Learning

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Multi-agent deep reinforcement learning-based robotic arm assembly research.

PloS one Feb 18, 2025
Due to the complexity and variability of application scenarios and the increasing demands for assembly, single-agent algorithms often face challenges in convergence and exhibit poor performance in robotic arm assembly processes. To address these issu...
Reinforcement, Psychology Reinforcement Machine Learning Humans Deep Learning Robotics Algorithms Computer Simulation
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Determining human resource management key indicators and their impact on organizational performance using deep reinforcement learning.

Scientific reports Feb 17, 2025
Performance-related indicators are crucial for evaluating and forecasting performance, enhancing decision-making efficiency, and establishing sustainable growth strategies. They motivate individuals and organizations, increase transparency, and accur...
Reinforcement Machine Learning Humans Deep Learning Efficiency, Organizational Neural Networks, Computer
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A Deep Reinforcement Learning-Based Feature Selection Method for Invasive Disease Event Prediction Using Imbalanced Follow-Up Data.

IEEE journal of biomedical and health informatics Feb 10, 2025
The machine learning-based model is a promising paradigm for predicting invasive disease events (iDEs) in breast cancer. Feature selection (FS) is an essential preprocessing technique employed to identify the pertinent features for the prediction mod...
Humans Reinforcement Machine Learning Breast Neoplasms Neoplasm Invasiveness Datasets as Topic Prognosis Female
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A continuous-action deep reinforcement learning-based agent for coronary artery centerline extraction in coronary CT angiography images.

Medical & biological engineering & computing Jan 31, 2025
The lumen centerline of the coronary artery allows vessel reconstruction used to detect stenoses and plaques. Discrete-action-based centerline extraction methods suffer from artifacts and plaques. This study aimed to develop a continuous-action-based...
Algorithms Coronary Angiography Deep Learning Image Processing, Computer-Assisted Humans Computed Tomography Angiography Reinforcement Machine Learning Coronary Artery Disease Artifacts Coronary Vessels
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Automating the optimization of proton PBS treatment planning for head and neck cancers using policy gradient-based deep reinforcement learning.

Medical physics Jan 31, 2025
BACKGROUND: Proton pencil beam scanning (PBS) treatment planning for head and neck (H&N) cancers is a time-consuming and experience-demanding task where a large number of potentially conflicting planning objectives are involved. Deep reinforcement le...
Automation Radiotherapy Dosage Proton Therapy Organs at Risk Radiotherapy Planning, Computer-Assisted Deep Learning Reinforcement Machine Learning Head and Neck Neoplasms Humans
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A safe-enhanced fully closed-loop artificial pancreas controller based on deep reinforcement learning.

PloS one Jan 27, 2025
Patients with type 1 diabetes and their physicians have long desired a fully closed-loop artificial pancreas (AP) system that can alleviate the burden of blood glucose regulation. Although deep reinforcement learning (DRL) methods theoretically enabl...
Insulin Infusion Systems Pancreas, Artificial Hypoglycemic Agents Hypoglycemia Reinforcement Machine Learning Insulin Algorithms Diabetes Mellitus, Type 1 Deep Learning Humans Blood Glucose
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Breast radiation therapy fluence painting with multi-agent deep reinforcement learning.

Medical physics Jan 23, 2025
BACKGROUND: The electronic compensation (ECOMP) technique for breast radiation therapy provides excellent dose conformity and homogeneity. However, the manual fluence painting process presents a challenge for efficient clinical operation.
Retrospective Studies Female Humans Breast Neoplasms Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Reinforcement Machine Learning Deep Learning
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Optimizing Biomimetic 3D Disordered Fibrous Network Structures for Lightweight, High-Strength Materials via Deep Reinforcement Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Jan 23, 2025
3D disordered fibrous network structures (3D-DFNS), such as cytoskeletons, collagen matrices, and spider webs, exhibit remarkable material efficiency, lightweight properties, and mechanical adaptability. Despite their widespread in nature, the integr...
Biomimetic Materials Reinforcement Machine Learning Animals Deep Learning Molecular Dynamics Simulation Silk Biomimetics
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Simulating fish autonomous swimming behaviours using deep reinforcement learning based on Kolmogorov-Arnold Networks.

Bioinspiration & biomimetics Jan 16, 2025
The study of fish swimming behaviours and locomotion mechanisms holds significant scientific and engineering value. With the rapid advancements in artificial intelligence, a new method combining deep reinforcement learning (DRL) with computational fl...
Animals Deep Learning Fishes Artificial Intelligence Computer Simulation Reinforcement, Psychology Reinforcement Machine Learning Swimming Hydrodynamics Neural Networks, Computer
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Novel deep reinforcement learning based collision avoidance approach for path planning of robots in unknown environment.

PloS one Jan 16, 2025
Reinforcement learning is a remarkable aspect of the artificial intelligence field with many applications. Reinforcement learning facilitates learning new tasks based on action and reward principles. Motion planning addresses the navigation problem f...
Deep Learning Robotics Reinforcement Machine Learning Reinforcement, Psychology Humans Artificial Intelligence Algorithms
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