Google researchers introduce ‘Internal RL,’ a technique that steers an models' hidden activations to solve long-horizon tasks ...

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

This repository showcases a hybrid control system combining Reinforcement Learning (Q-Learning) and Neural-Fuzzy Systems to dynamically tune a PID controller for an Autonomous Underwater Vehicle (AUV) ...

AgiBot announced a key milestone this week with the successful deployment of its Real-World Reinforcement Learning system in a manufacturing pilot with Longcheer Technology. The pilot project marks ...

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...

Parents visiting their children’s kindergarten class for the first time may think they’ve arrived at the wrong room, especially if they expect it to resemble the kindergarten they attended as ...

Abstract: Integrating learning-based techniques, especially reinforcement learning, into robotics is promising for solving complex problems in unstructured environments. Most of the existing ...

AI coding tools are getting better fast. If you don’t work in code, it can be hard to notice how much things are changing, but GPT-5 and Gemini 2.5 have made a whole new set of developer tricks ...

Companies investing millions in generative AI may soon find themselves stalled—not by the technology’s limits, but by their people’s. As generative AI becomes more ubiquitous, a paradox has emerged: ...

For years, Big Tech CEOs have touted visions of AI agents that can autonomously use software applications to complete tasks for people. But take today’s consumer AI agents out for a spin, whether it’s ...