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

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

Deep reinforcement learning leverages the learning capacity of deep neural networks to tackle problems that were too complex for classic RL techniques.

AlphaGo and AlphaZero both rely on reinforcement learning to train. They also use deep neural networks as part of the reinforcement learning network, to predict outcome probabilities.

Neural networks can better model high-level abstractions during the learning process, and combining the two techniques together has yielded state-of-the-art results across many problem areas.

Reinforcement learning is a subset of machine learning. It enables an agent to learn through the consequences of actions in a specific environment. It can be used to teach a robot new tricks, for ...

Such networks are being used in chemistry and drug discovery as well, for example to predict the binding affinities of proteins and ligands based on their structures. In combination with a technique ...

Deep neural networks will move past their shortcomings without help from symbolic artificial intelligence, three pioneers of deep learning argue in a paper published in the July issue of the ...