Abstract: This article explores the application of reinforcement learning (RL) strategy to achieve an adaptive fixed-time (FxT) optimized formation control of uncertain nonlinear multiagent systems.
You will be redirected to our submission process. The accelerating pace of global environmental change driven by climate change, biodiversity loss, land degradation, and urbanization demands ...
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Researchers use AI to evaluate a systematic framework to describe molecular order in liquid water
Water is the most abundant liquid on Earth's surface, and it is highly anomalous compared with other liquids because it ...
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Deep-ocean heat is creeping toward Antarctica’s ice, a decades-long study warns
Warm water from the deep Southern Ocean has been steadily creeping closer to Antarctica’s ice shelves over the past four ...
Abstract: A machine-learning-assisted optimization (MLAO) method for antenna geometry design (AGD) (MLAO-AGD) is proposed. By combining machine learning (ML) methods, including a convolutional neural ...
As energy companies push AI deeper into industrial operations, success increasingly depends on governance, trusted data, and ...
Teams are using AI to analyze data, speed up engineering work, and give drivers an edge. Now the FIA is writing rules to keep ...
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