Li, H. (2026) A Study on the Impact of New Media on College Students’ Oral English Learning —Taking English Content Creators on Bilibili as an Example. Open Access Library Journal, 13, 1-18. doi: ...

Watch an AI agent learn how to balance a stick—completely from scratch—using reinforcement learning! This project walks you ...

The Allen Institute for AI (Ai2) recently released what it calls its most powerful family of models yet, Olmo 3. But the company kept iterating on the models, expanding its reinforcement learning (RL) ...

I asked attendees for their takeaways from this year’s NeurIPS in San Diego. I asked attendees for their takeaways from this year’s NeurIPS in San Diego. is a contributing writer and author of the ...

RLinf is a flexible and scalable open-source RL infrastructure designed for Embodied and Agentic AI. The 'inf' in RLinf stands for Infrastructure, highlighting its role as a robust backbone for ...

In this tutorial, we explore Online Process Reward Learning (OPRL) and demonstrate how we can learn dense, step-level reward signals from trajectory preferences to solve sparse-reward reinforcement ...

Researchers uncovered how estrogen subtly reshapes learning by strengthening dopamine reward signals in the brain. Rats learned faster when estrogen levels were high and struggled when the hormone’s ...

Download PDF Join the Discussion View in the ACM Digital Library Deep reinforcement learning (DRL) has elevated RL to complex environments by employing neural network representations of policies. 1 It ...

Sutton believes Reinforcement Learning is the Path to to Intelligence via Experience. Sutton defines intelligence as the computational part of the ability to achieve goals. It is rooted in a stream of ...

Imagine knowing that the stock market will likely crash in three years, that extreme weather will destroy your home in eight or that you will have a debilitating disease in 15—but that you can take ...