For decades, dopamine has been celebrated in neuroscience as the quintessential "reward molecule"—a chemical herald of ...

The ability of computers to learn on their own by using data is known as machine learning. It is closely related to ...

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

Request To Download Free Sample of This Strategic Report @- The global reinforcement learning market is experiencing a period of rapid growth, with revenue estimated to increase from approximately $3 ...

Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, ...

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

AWS, Cisco, CoreWeave, Nutanix and more make the inference case as hyperscalers, neoclouds, open clouds, and storage go ...

Crucially, detection and response must be unified across identity and data layers. An alert about unusual data access is meaningless if it is not correlated with identity risk signals. Autonomous ...

Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to underwater cables—and is critical for safe renewable energy development.

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents. We provide implementations ...