Abstract: Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has recently been able to solve a wide range of complex ...

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In the fourth and last component of our “The Mind’s Mirror” book review, let’s look at the appendix, a timeline in AI ...

Artificial intelligence enhances the network capability with automatic and adaptive adjustment. Reinforcement learning (RL) and deep reinforcement learning (DRL) are two powerful techniques in ...

@article{kostrikov2021iql, title={Offline Reinforcement Learning with Implicit Q-Learning}, author={Ilya Kostrikov and Ashvin Nair and Sergey Levine}, year={2021 ...

Neuromorphic hardware with spiking neural network (SNN) architecture utilizes insights from biological phenomena to offer encouraging solutions. Previous studies have proposed reinforcement learning ...

Traditional reinforcement learning algorithms lack exploration of the environment, and the strategies learned by the agent may not generalize well to other different environments. To address these ...

At the intersection of biology and AI, Somite.ai is pioneering the future of repairing human bodies by applying the ...