Decentralized Reinforcement Learning for Asymmetric Gene Network Interventions. [PDF]
IEEE Trans Comput Biol BioinformHosseini SH, Imani M.
europepmc +1 more source
Reinforcement learning for whole-building HVAC control and demand response
, 2020 Donald Azuatalam +3 more
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Hydrogel‐Based Functional Materials: Classifications, Properties, and Applications
Advanced Materials Technologies, EarlyView.Conductive hydrogels have emerged as promising materials for smart wearable devices due to their outstanding flexibility, multifunctionality, and biocompatibility. This review systematically summarizes recent progress in their design strategies, focusing on monomer systems and conductive components, and highlights key multifunctional properties such as
Zeyu Zhang, Zao Cheng, Patrizio Raffa
wiley +1 more source
Information Bottleneck-Enhanced Reinforcement Learning for Solving Operation Research Problems. [PDF]
Sensors (Basel)Xi R, Ni Y, Wu W.
europepmc +1 more source
Adhesive Double‐Network Granular Organogel E‐Skin
Advanced Materials Technologies, EarlyView.We introduce a double‐network granular organogel adhesive for electronic skin, overcoming adhesion and strength trade‐offs. It provides reversible, robust bonding and ionic conductivity, enabling wearable and soft robotic e‐skin. Thanks to the e‐skin adhesive, a soft robotic trunk can recognize touch, temperature, humidity, and acidity.
Antonia Georgopoulou +4 more
wiley +1 more source
A reinforcement learning algorithm to optimize resource utilization in combat casualty care. [PDF]
Sci RepSubramaniyan M +4 more
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Exploring the Application of Reinforcement Learning in the Path Planning Algorithm of UAVs [PDF]
Xiaoxu Wang
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Excitonic Landscapes in Monolayer Lateral Heterostructures Revealed by Unsupervised Machine Learning
Advanced Optical Materials, EarlyView.Hyperspectral photoluminescence data from graded MoxW1 − xS2 alloys and monolayer MoS2–WS2 lateral heterostructures are analyzed using unsupervised machine learning. The combined use of PCA, t‐SNE, and DBSCAN uncovers distinct excitonic regions that trace how composition, strain, and defects modulate optical responses in these 2D materials.
Maninder Kaur +4 more
wiley +1 more source
Adapting virtual agent interaction style with reinforcement learning to enhance affective engagement. [PDF]
Front Digit HealthTamantini C +5 more
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UniROS: ROS-Based Reinforcement Learning Across Simulated and Real-World Robotics [PDF]
Jayasekara Kapukotuwa +3 more
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