At the core of Industry 4.0, the smart factory integrates automation, mass customization, and self-organization into a highly ...

a reinforcement learner is able to perform actions in an environment, and get rewards or penalties from their actions the goal of a reinforcement learner is to maximize the rewards the get in some ...

Machine learning (ML) might be considered the core subset of artificial intelligence (AI), and reinforcement learning may be the quintessential subset of ML that people imagine when they think of AI.

OpenAI researchers have published a new study examining whether reinforcement learning (RL) can be used not only to improve ...

Reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by interacting with an environment. Think of it like training a dog: every time the dog sits on ...

Prof Ambuj Tewari from the University of Michigan explains the origins of reinforcement learning and why it’s so valuable in AI research and development. Understanding intelligence and creating ...

Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...

Deep generative neural networks have been used increasingly in computational chemistry for de novo design of molecules with desired properties. Many deep learning approaches employ reinforcement ...

This study investigates the effects of error-based and reinforcement training on the acquisition and long-term retention of free throw accuracy in basketball. Sixty participants were divided into four ...