Reinforcement learning techniques could be the keys to integrating robots — who use machine learning to output more than words — into the real world.

Reinforcement Learning (RL): A machine learning paradigm in which agents learn to make decisions by performing actions and receiving feedback in the form of rewards or penalties.

An overview of reinforcement learning and its meaning and use. ... RL is widely used in fields such as robotics, game playing, and autonomous systems, where dynamic decision-making is essential.

Amazon today launched SageMaker Reinforcement Learning (RL) Kubeflow Components, a toolkit supporting the company’s AWS RoboMaker service for orchestrating robotics workflows. Amazon says that ...

Boston Dynamics partners with Robotics & AI Institute to develop reinforcement learning for humanoid robots February 9, 2025 by Mark Allinson . Tuesday, 02 January 2024 12:17 GMT.

Legged robots, which are often inspired by animals and insects, could help humans to complete various real-world tasks, for instance delivering parcels or monitoring specific environments. In ...

Stoica works on robotics and reinforcement learning at UC Berkeley’s RISELab, and if you’re a developer working today, then you’ve likely used or come across some of his work that has built ...

Clustering-based approach accelerates AI learning in robotics and gaming. ... Clustered Reinforcement Learning, Frontiers of Computer Science (2024). DOI: 10.1007/s11704-024-3194-1.

With no well-specified rewards and state transitions that take place in a myriad of ways, training a robot via reinforcement learning represents perhaps the most complex arena for machine learning.