AI agents learn to juggle cloud data centers in real time
A multi-agent reinforcement learning framework schedules tasks across a 2000-node big data cluster with 92.4 percent success and millisecond-scale latency, ...
A multi-agent reinforcement learning framework schedules tasks across a 2000-node big data cluster with 92.4 percent success and millisecond-scale latency, ...
Researchers have developed an AI-driven scheduler that predicts congestion in edge-cloud environments before it happens, cutting response times and protecting ...
A new study in AI & Society argues that Thomas Aquinas's virtues of justice, prudence, and charity can guide the ...
Researchers have combined a digital twin simulation platform with federated multi-agent reinforcement learning to optimize resource allocation across satellite, UAV, ...
A new comprehensive survey in Cluster Computing systematically compares how deep reinforcement learning algorithms are transforming task scheduling and offloading ...
A hybrid deep learning framework combining AlexNet and Ant Colony Optimization significantly improves routing, delay, and energy efficiency in cloud-based ...
A systematic review of 80 peer-reviewed studies reveals that AI, especially deep reinforcement learning, is rapidly transforming how serverless cloud ...
A new analysis of more than five decades of Chicago homicide data shows that murders across police districts fit a ...
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© 2026 Scienmag - Science Magazine