Results 181 to 190 of about 198,528 (317)

Editorial: Reinforcement learning for real-world robot navigation. [PDF]

Front Robot AI
Wang P, Li X, Zhu M, Ma J.
europepmc   +1 more source

At Home Detection of Ovarian Health Biomarker in Menstruation Blood

Advanced Materials Technologies, EarlyView.
A lateral flow assay enables the detection of anti‐Müllerian hormone directly in unprocessed menstrual blood using silica‐gold nanoshells and smartphone‐assisted machine learning analysis. The platform supports decentralized, user‐operated testing in wearable and dipstick formats, highlighting the potential of menstrual blood as a non‐invasive matrix ...
Lucas Dosnon, Thomas Rduch, Salma Sherif Azer, Inge K. Herrmann   +3 more
wiley   +1 more source

Competitive swarm reinforcement learning improves stability and performance of deep reinforcement learning. [PDF]

Sci Rep
Huang X, Luo W, Li L, Zhang H, Jiang H, Gao X.   +5 more
europepmc   +1 more source

Acquiring musculoskeletal skills with curriculum-based reinforcement learning

Efficient musculoskeletal simulators and powerful learning algorithms provide computational tools to tackle the grand challenge of understanding biological motor control.
Chiappa, Alberto, Pouget, Alexandre, Ingster, Abigaïl Rebecca Lise, Tano, Pablo, Patel, Nisheet, Mathis, Alexander   +5 more
core   +1 more source

The Evolution of Aerosol Jet Printing, A Review: Enhancing Material Versatility and Improvements for Next‐Generation Applications

Advanced Materials Technologies, EarlyView.
Aerosol Jet Printing (AJP) has emerged as a versatile additive manufacturing technique for high‐resolution, conformal, and multi‐material printing. This review highlights advances in printable materials, substrate compatibility, post‐processing, characterization, and process innovations, while critically discussing current challenges and future ...
Chandrachur Chatterjee, Rocco Lupoi, Michael J. Gibbons   +2 more
wiley   +1 more source

Robust Path Planning via Deep Reinforcement Learning. [PDF]

Sensors (Basel)
Kang D, Park J, Kim P.
europepmc   +1 more source

Data‐Efficient Electromagnetic Surrogate Solver Through Dissipative Relaxation Transfer Learning

Advanced Optical Materials, EarlyView.
Dissipative relaxation transfer learning (DIRTL) enables data‐efficient training of electromagnetic surrogate solvers by pretraining data generated with artificial material loss before fine‐tuning on target lossless data. The framework suppresses resonant outlier effects during early training, allowing effective adaptation to high‐amplitude resonances ...
Sunghyun Nam, Chan Y. Park, Min Seok Jang   +2 more
wiley   +1 more source

Multi-task procedural content generation with reinforcement learning. [PDF]

Sci Rep
Nekahdari A, Kouzehkonani ED, Saeedi N, Shirini K, Gharehveran SS.   +4 more
europepmc   +1 more source

Learning Multimodal Transition Dynamics for Model-Based Reinforcement Learning

, 2017
In this paper we study how to learn stochastic, multimodal transition dynamics in reinforcement learning (RL) tasks. We focus on evaluating transition function estimation, while we defer planning over this model to future work.
Jonker, C.M. (author), Moerland, T.M. (author), Broekens, D.J. (author)   +2 more
core  

Soft Robotic Excretory Care Simulator for Nursing Education: Functional and Perceptual Biomimetics Approach

Advanced Robotics Research, EarlyView.
A soft robotic simulator is developed to replicate the digital removal of feces (DRF), a sensitive yet essential nursing procedure. Integrating soft actuators, sensors, and a realistic rectal model, the simulator balances functional fidelity with perceptual realism. Engineering evaluations and nurse feedback confirm its potential to enhance training in
Shoko Miyagawa, Sota Suzuki, Shizuka Watanabe, Zebing Mao, Young Ah Seong, Toshinori Fujie, Tatsuhiro Horii, Kenjiro Tadakuma, Koichi Suzumori, Hiroyuki Nabae, Shingo Maeda   +10 more
wiley   +1 more source