Results 41 to 50 of about 137,924 (252)

Multi-task Deep Reinforcement Learning with PopArt

, 2018
The reinforcement learning community has made great strides in designing algorithms capable of exceeding human performance on specific tasks. These algorithms are mostly trained one task at the time, each new task requiring to train a brand new agent ...
Czarnecki, Wojciech, Espeholt, Lasse, Hessel, Matteo, Schmitt, Simon, Soyer, Hubert, van Hasselt, Hado   +5 more
core   +1 more source

A Scoping Review on Artificial Intelligence–Supported Interventions for Nonpharmacologic Management of Chronic Rheumatic Diseases

Arthritis Care &Research, EarlyView.
This review summarizes artificial intelligence (AI)‐supported nonpharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose, and current evidence base. We searched Embase, PubMed, Cochrane, and Scopus databases for studies describing AI‐supported interventions for adults with chronic rheumatic diseases.
Nirali Shah, Alexis Castellanos, Yen Chen, John Piette, Amy Bucher, Susan Murphy   +5 more
wiley   +1 more source

A Cooperative Multi-Agent Reinforcement Learning Method Based on Coordination Degree

IEEE Access, 2021
Multi-agent reinforcement learning (MARL) has become a prevalent method for solving cooperative problems owing to its tractable implementation and task distribution. The goal of the MARL algorithms for fully cooperative scenarios is to obtain the optimal
Haoyan Cui, Zhen Zhang
doaj   +1 more source

Multi-agent reinforcement learning for route guidance system [PDF]

, 2011
Nowadays, multi-agent systems are used to create applications in a variety of areas, including economics, management, transportation, telecommunications, etc. Importantly, in many domains, the reinforcement learning agents try to learn a task by directly
Arokhlo, Mortaza Zolfpour, Mohd. Hashim, Siti Zaiton, Selamat, Ali, Selamat, Md. Hafiz   +3 more
core  

Advancing Electronic Application of Coordination Solids: Enhancing Electron Transport and Device Integration via Surface‐Mounted MOFs (SURMOFs)

Advanced Functional Materials, EarlyView.
The layer‐by‐layer (LbL) assembly of coordination solids, enabled by the surface‐mounted metal‐organic framework (SURMOF) platform, is on the cusp of generating the organic counterpart of the epitaxy of inorganics. The programmable and sequential SURMOF protocol, optimized by machine learning (ML), is suited for accessing high‐quality thin films of ...
Zhengtao Xu, Christof Wöll, Stefan Bräse   +2 more
wiley   +1 more source

Dual Preference Learning for Multi-Agent Reinforcement Learning

IEEE Access
Designing effective reward functions is fundamental challenging in reinforcement learning, especially in complex multi-agent systems with intricate credit assignment.
Sehyeok Kang, Minu Kim, Jihwan Oh, Se-Young Yun   +3 more
doaj   +1 more source

Multi-agent Reinforcement Learning Algorithm Based on AI Planning [PDF]

Jisuanji kexue
At present,deep reinforcement learning algorithms have made a lot of achievements in various fields.However,in the field of multi-agent task,agents are often faced with non-stationary environment with larger state-action space and sparse rewards,low ...
XIN Yuanxia, HUA Daoyang, ZHANG Li
doaj   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Region‐to‐Region Unidirectional Connection In Vitro Brain Model for Studying Directional Propagation of Neuropathologies

Advanced Functional Materials, EarlyView.
A unidirectional cerebral organoid–organoid neural circuit is established using a microfluidic platform, enabling controlled directional propagation of electrical signals, neuroinflammatory cues, and neurodegenerative disease–related proteins between spatially separated organoids.
Kyeong Seob Hwang, Hui‐Wen Liu, Hyogeun Shin, Hyun Wook Kang, Minjin Kang, Jongbaeg Kim, Il‐Joo Cho, Nakwon Choi, Seok Chung, Hong Nam Kim   +9 more
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