Traffic congestion, fuel consumption, and emissions also offer quantifiable performance indicators, making mobility uniquely ...
In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...
Most current autonomous driving systems rely on single-agent deep learning models or end-to-end neural networks. While ...
Hexagon Robotics is pleased to announce a strategic partnership with Microsoft aimed at advancing humanoid robots with a focus on: Redefini ...
AZoSensors on MSN
Energy-aware protocol cuts power use in green IoT networks
Researchers introduce the EAVM protocol, achieving 17 % lower energy use and 20 % longer network lifetime in IoT systems with advanced virtualization techniques.
Abstract: Deep reinforcement learning (DRL) facilitates efficient interaction with complex environments by enabling continuous optimization strategies and providing agents with autonomous learning ...
Morning Overview on MSN
Scientists build a ‘periodic table’ for AI models
Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a ...
In a new study, Chinese researchers tested whether monitoring passengers’ brain activity could help self-driving systems make ...
In the race against the "Carbon Cliff", AI is becoming an essential tool for balancing the economic equation. AI integration ...
Nearly a century ago, psychologist B.F. Skinner pioneered a controversial school of thought, behaviorism, to explain human and animal behavior. Behaviorism directly inspired modern reinforcement ...
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