Abstract: Algorithmic stock trading has improved tremendously, with Reinforcement Learning (RL) algorithms being more adaptable than classic approaches like mean reversion and momentum. However, ...
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 ...
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