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Reinforcement Machine Learning

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Shared autonomy between human electroencephalography and TD3 deep reinforcement learning: A multi-agent copilot approach.

Annals of the New York Academy of Sciences 40159374
Deep reinforcement learning (RL) algorithms enable the development of fully autonomous agents that can interact with the environment. Brain-computer interface (BCI) systems decipher human implicit brain signals regardless of the explicit environment....
Algorithms Brain Brain-Computer Interfaces Deep Learning Electroencephalography Humans Reinforcement Machine Learning Reinforcement, Psychology
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Deep reinforcement learning for decision making of autonomous vehicle in non-lane-based traffic environments.

PloS one 40238783
Existing research on decision-making of autonomous vehicles (AVs) has mainly focused on normal road sections, with limited exploration of decision-making in complex traffic environments without lane markings. Taking toll plaza diverging area as an ex...
Algorithms Automobile Driving Automobiles Computer Simulation Decision Making Deep Learning Humans Reinforcement Machine Learning
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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 40030195
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...
Breast Neoplasms Datasets as Topic Female Humans Neoplasm Invasiveness Prognosis Reinforcement Machine Learning
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SmartAPM framework for adaptive power management in wearable devices using deep reinforcement learning.

Scientific reports 40011572
Wearable devices face a significant challenge in balancing battery life with performance, often leading to frequent recharging and reduced user satisfaction. In this paper, we introduce the SmartAPM (Smart Adaptive Power Management) framework, a nove...
Algorithms Deep Learning Electric Power Supplies Humans Reinforcement Machine Learning Wearable Electronic Devices
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Deep reinforcement learning can promote sustainable human behaviour in a common-pool resource problem.

Nature communications 40121193
A canonical social dilemma arises when resources are allocated to people, who can either reciprocate with interest or keep the proceeds. The right resource allocation mechanisms can encourage levels of reciprocation that sustain the commons. Here, in...
Cooperative Behavior Deep Learning Game Theory Humans Neural Networks, Computer Reinforcement Machine Learning Reinforcement, Psychology Resource Allocation Trust
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Pixel level deep reinforcement learning for accurate and robust medical image segmentation.

Scientific reports 40064951
Existing deep learning methods have achieved significant success in medical image segmentation. However, this success largely relies on stacking advanced modules and architectures, which has created a path dependency. This path dependency is unsustai...
Algorithms Deep Learning Humans Image Processing, Computer-Assisted Reinforcement Machine Learning
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Modeling crash avoidance behaviors in vehicle-pedestrian near-miss scenarios: Curvilinear time-to-collision and Mamba-driven deep reinforcement learning.

Accident; analysis and prevention 40043346
Interactions between vehicle-pedestrian at intersections often lead to safety-critical situations. This study aims to model the crash avoidance behaviors of vehicles during interactions with pedestrians in near-miss scenarios, contributing to the dev...
Accidents, Traffic Algorithms Avoidance Learning Computer Simulation Deep Learning Environment Design Humans Models, Theoretical Pedestrians Reinforcement Machine Learning Safety Time Factors Unmanned Aerial Devices
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Deep reinforcement learning for Type 1 Diabetes: Dual PPO controller for personalized insulin management.

Computers in biology and medicine 40239234
BACKGROUND: Managing blood glucose levels in Type 1 Diabetes Mellitus (T1DM) is essential to prevent complications. Traditional insulin delivery methods often require significant patient involvement, limiting automation. Reinforcement Learning (RL)-b...
Adult Blood Glucose Computer Simulation Deep Learning Diabetes Mellitus, Type 1 Female Humans Hypoglycemic Agents Insulin Insulin Infusion Systems Male Pancreas, Artificial Precision Medicine Reinforcement Machine Learning
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Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning.

Nature communications 40234405
Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cell carcinoma. However, our understanding of ccRCC risk genes remains limited. This gap in knowledge poses challenges to the effective diagnosis and treatment of ccRCC. To a...
Carcinoma, Renal Cell Computational Biology Deep Learning ErbB Receptors Genetic Predisposition to Disease Humans Kidney Neoplasms Markov Chains Reinforcement Machine Learning Risk Factors
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CNRein: an evolution-aware deep reinforcement learning algorithm for single-cell DNA copy number calling.

Genome biology 40197547
Low-pass single-cell DNA sequencing technologies and algorithmic advancements have enabled haplotype-specific copy number calling on thousands of cells within tumors. However, measurement uncertainty may result in spurious CNAs inconsistent with real...
Algorithms Breast Neoplasms Deep Learning DNA Copy Number Variations Female Humans Ovarian Neoplasms Reinforcement Machine Learning Sequence Analysis, DNA Single-Cell Analysis
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