At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward. Similar to toddlers learning how to walk who adjust actions based on the ...

Reinforcement-learning algorithms 1,2 are inspired by our understanding of decision making in humans and other animals in which learning is supervised through the use of reward signals in response to ...

Progress in self-­driving cars and other forms of automation will slow dramatically unless machines can hone skills through experience. Inside a simple computer simulation, a group of self-driving ...

Deep reinforcement learning is having a superstar moment. Powering smarter robots. Simulating human neural networks. Trouncing physicians at medical diagnoses and crushing humanity’s best gamers at Go ...

Deep Reinforcement Learning (DRL) is a subfield of machine learning that combines neural networks with reinforcement learning techniques to make decisions in complex environments. It has been applied ...

Researchers have proposed a personalized longitudinal motion planning policy for intelligent vehicles that combines reinforcement learning with imitation learning. The approach is designed to reduce ...