The core of quantum network research lies in efficiently and reliably establishing entanglement between nodes; however, the challenges of maintaining fragile quantum states are far more complex than ...

The core of this research lies in the combination of Graph Neural Networks (GNN) and Reinforcement Learning to achieve coordinated control of up to eight robotic arms, enabling efficient and collision ...

A U.S. Naval Research Laboratory (NRL) research team successfully conducted the first reinforcement learning (RL) control of ...

Deep reinforcement learning is one of the most interesting branches ofartificial intelligence. It is behind some of the most remarkable achievements of the AI community, including beating human ...

Google DeepMind and Intrinsic developed AI that uses graph neural networks and reinforcement learning to automate multi-robot ...

In operation and maintenance, which accounts for the majority of research, IoT sensors and Digital Twins enable real-time monitoring of building systems. When coupled with AI, these technologies drive ...

Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of ...

It was not long ago that the world watched World Chess Champion Garry Kasparov lose a decisive match against a supercomputer. IBM’s Deep Blue embodied the state of the art in the late 1990s, when a ...

Despite the huge contributions of deep learning to the field of artificial intelligence, there’s something very wrong with it: It requires huge amounts of data. This is one thing that both the ...

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