Results 61 to 70 of about 10,350,910 (281)

QiMARL: Quantum-Inspired Multi-Agent Reinforcement Learning Strategy for Efficient Resource Energy Distribution in Nodal Power Stations

AI
The coupling of quantum computing with multi-agent reinforcement learning (MARL) provides an exciting direction to tackle intricate decision-making tasks in high-dimensional spaces.
Sapthak Mohajon Turjya, Anjan Bandyopadhyay, M. Shamim Kaiser, Kanad Ray   +3 more
doaj   +1 more source

Advances in Solution‐Processed Textile Triboelectric Nanogenerators: Ink Formation, Processing Strategies, Applications, and Challenges

Advanced Functional Materials, EarlyView.
Advanced ink systems for solution‐processed textile triboelectric nanogenerators are systematically summarized, spanning conductive, tribo‐negative, and tribo‐positive layers. By connecting ink chemistry, deposition methods, and device function, the present review reveals the key governing principles of solution development and highlights practical ...
Xinlong Sun, Stephen Beeby
wiley   +1 more source

Multi-AUV Hunting Strategy Based on Regularized Competitor Model in Deep Reinforcement Learning

Journal of Marine Science and Engineering
Reinforcement learning has made significant progress in single-agent applications, but it still faces various challenges in multi-agent scenarios. This study investigates the application of reinforcement learning algorithms in a competitive game scenario
Yancheng Sui, Zhuo Wang, Guiqiang Bai, Hao Lu   +3 more
doaj   +1 more source

Review of Attention Mechanisms in Reinforcement Learning [PDF]

Jisuanji kexue yu tansuo
In recent years, the combination of reinforcement learning and attention mechanisms has attracted an increasing attention in algorithmic research field.
XIA Qingfeng, XU Ke'er, LI Mingyang, HU Kai, SONG Lipeng, SONG Zhiqiang, SUN Ning
doaj   +1 more source

Heterogeneity in Multi-Agent Reinforcement Learning

Proceedings of the 25th International Conference on Autonomous Agents and Multiagent Systems
Heterogeneity is a fundamental property in multi-agent reinforcement learning (MARL), which is closely related not only to the functional differences of agents, but also to policy diversity and environmental interactions. However, the MARL field currently lacks a rigorous definition and deeper understanding of heterogeneity.
Tianyi Hu, Zhiqiang Pu, Yuan Wang, Tenghai Qiu, Min Chen 0038, Xin Yu 0009   +5 more
openaire   +3 more sources

Multi-Agent Common Knowledge Reinforcement Learning

CoRR, 2018
Advances in Neural Information Processing Systems, 9924 ...
de Witt, C, Foerster, J, Farquhar, G, Torr, PHS, Boehmer, W, Whiteson, S   +5 more
openaire   +4 more sources

Nitride MXenes Beyond Carbides: Bridging the Gap Between Computational Prediction and Experimental Realization

Advanced Functional Materials, EarlyView.
Nitride MXenes remain constrained by a persistent gap between computational prediction and experimental realization. This Review identifies the thermodynamic, kinetic, and chemical barriers limiting their synthesis, critically evaluates emerging fabrication routes, and proposes a multidimensional computational‐experimental framework to accelerate the ...
Naresh Varnakavi, Masoud Soroush
wiley   +1 more source

FLDQN: Cooperative Multi-Agent Federated Reinforcement Learning for Solving Travel Time Minimization Problems in Dynamic Environments Using SUMO Simulation

Sensors
The increasing volume of traffic has led to severe challenges, including traffic congestion, heightened energy consumption, increased air pollution, and prolonged travel times.
Abdul Wahab Mamond, Majid Kundroo, Seong-eun Yoo, Seonghoon Kim, Taehong Kim   +4 more
doaj   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Advances in 3D Bioprinting for Breast Cancer Modeling: Tumor Microenvironment, Metastasis, and Drug Screening

Advanced Healthcare Materials, EarlyView.
Three‐dimensional bioprinting transforms breast cancer modeling from simple constructs into spatially organized, multicellular, perfused, and patient‐derived platforms. This review shows how bioinks, cellular composition, architecture, and flow govern tumor behavior and drug response, while revealing why complexity alone is insufficient without ...
Mustafa Nakipoglu, Mahboobeh Mahmoodi, Ehsanul Hoque Apu, Fahimeh Shahabipour, Sibel Emir Diltemiz, Sanjib Saha, Halima Alem, Nureddin Ashammakhi   +7 more
wiley   +1 more source