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Reinforcement Machine Learning

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Robotic navigation with deep reinforcement learning in transthoracic echocardiography.

International journal of computer assisted radiology and surgery 39304590
PURPOSE: The search for heart components in robotic transthoracic echocardiography is a time-consuming process. This paper proposes an optimized robotic navigation system for heart components using deep reinforcement learning to achieve an efficient ...
Algorithms Deep Learning Echocardiography Humans Mitral Valve Reinforcement Machine Learning Robotic Surgical Procedures Surgery, Computer-Assisted
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Autonomous countertraction for secure field of view in laparoscopic surgery using deep reinforcement learning.

International journal of computer assisted radiology and surgery 39285110
PURPOSE: Countertraction is a vital technique in laparoscopic surgery, stretching the tissue surface for incision and dissection. Due to the technical challenges and frequency of countertraction, autonomous countertraction has the potential to signif...
Computer Simulation Deep Learning Humans Laparoscopy Neural Networks, Computer Phantoms, Imaging Reinforcement Machine Learning
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Protocol for artificial intelligence-guided neural control using deep reinforcement learning and infrared neural stimulation.

STAR protocols 39705145
Closed-loop neural control is a powerful tool for both the scientific exploration of neural function and for mitigating deficiencies found in open-loop deep brain stimulation (DBS). Here, we present a protocol for artificial intelligence-guided neura...
Animals Artificial Intelligence Deep Brain Stimulation Deep Learning Infrared Rays Rats Reinforcement Machine Learning Reinforcement, Psychology
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AlphaMut: A Deep Reinforcement Learning Model to Suggest Helix-Disrupting Mutations.

Journal of chemical theory and computation 39702999
Helices are important secondary structural motifs within proteins and are pivotal in numerous physiological processes. While amino acids (AA) such as alanine and leucine are known to promote helix formation, proline and glycine disfavor it. Helical s...
Deep Learning Models, Molecular Mutation Protein Structure, Secondary Proteins Reinforcement Machine Learning Thermodynamics
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A fully value distributional deep reinforcement learning framework for multi-agent cooperation.

Neural networks : the official journal of the International Neural Network Society 39693677
Distributional Reinforcement Learning (RL) extends beyond estimating the expected value of future returns by modeling its entire distribution, offering greater expressiveness and capturing deeper insights of the value function. To leverage this advan...
Algorithms Cooperative Behavior Deep Learning Humans Neural Networks, Computer Reinforcement Machine Learning Reinforcement, Psychology
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ReLMM: Reinforcement Learning Optimizes Feature Selection in Modeling Materials.

Journal of chemical information and modeling 39689297
A challenge to materials discovery is the identification of the physical features that are most correlated to a given target material property without redundancy. Such variables necessarily comprise the optimal search domain in subsequent material de...
Models, Chemical Reinforcement Machine Learning
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Simulating fish autonomous swimming behaviours using deep reinforcement learning based on Kolmogorov-Arnold Networks.

Bioinspiration & biomimetics 39752883
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 Artificial Intelligence Computer Simulation Deep Learning Fishes Hydrodynamics Neural Networks, Computer Reinforcement Machine Learning Reinforcement, Psychology Swimming
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Hybrid Control Policy for Artificial Pancreas via Ensemble Deep Reinforcement Learning.

IEEE transactions on bio-medical engineering 39208051
OBJECTIVE: The artificial pancreas (AP) shows promise for closed-loop glucose control in type 1 diabetes mellitus (T1DM). However, designing effective control policies for the AP remains challenging due to complex physiological processes, delayed ins...
Blood Glucose Computer Simulation Deep Learning Diabetes Mellitus, Type 1 Humans Insulin Pancreas, Artificial Reinforcement Machine Learning
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Deep Reinforcement Learning in Human Activity Recognition: A Survey and Outlook.

IEEE transactions on neural networks and learning systems 38373132
Human activity recognition (HAR) is a popular research field in computer vision that has already been widely studied. However, it is still an active research field since it plays an important role in many current and emerging real-world intelligent s...
Deep Learning Human Activities Humans Neural Networks, Computer Pattern Recognition, Automated Reinforcement Machine Learning Reinforcement, Psychology
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