IEEE

Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications

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

The reinforcement gap — or why some AI skills improve faster than others

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 ...
IEEE

Optimization of Reinforcement Learning Using Quantum Computation

Abstract: Exploring the convergence of quantum computing and machine learning, this paper delves into Quantum Reinforcement Learning (QRL) with a specific focus on Variational Quantum Circuits (VQC).
GitHub

robust-reinforcement-learning

This repo contains the repeatability package of the paper "Training Verifiably Robust Agnets Using Set-Based Reinforcement Learning", Wendl et. al, 2024.
The New York Times

Parents, Your Job Has Changed in the A.I. Era

Ms. Anderson and Ms. Winthrop are the authors of “The Disengaged Teen: Helping Kids Learn Better, Feel Better, and Live Better.” As the new school year gets underway, artificial intelligence is ...
marktechpost

DSRL: A Latent-Space Reinforcement Learning Approach to Adapt Diffusion Policies in Real ...

Robotic control systems have made significant progress through methods that replace hand-coded instructions with data-driven learning. Instead of relying on explicit programming, modern robots learn ...
acm.org

Developing the Foundations of Reinforcement Learning

The examples are nothing if not relatable: preparing breakfast, or playing a game of chess or tic-tac-toe. Yet the idea of learning from the environment and taking steps that progress toward a goal ...
marktechpost

Vision-R1: Redefining Reinforcement Learning for Large Vision-Language Models

Large Vision-Language Models (LVLMs) have made significant strides in recent years, yet several key limitations persist. One major challenge is aligning these models effectively with human ...
Wired

Pioneers of Reinforcement Learning Win the Turing Award

In the 1980s, Andrew Barto and Rich Sutton were considered eccentric devotees to an elegant but ultimately doomed idea—having machines learn, as humans and animals do, from experience. Decades on, ...
Frontiers

Reinforcement learning-based multi-model ensemble for ocean waves forecasting

This study addresses the challenges of uncertainty in wave simulations within complex and dynamic ocean environments by proposing a reinforcement learning-based model ensemble algorithm. The algorithm ...
unite

The Many Faces of Reinforcement Learning: Shaping Large Language Models

In recent years, Large Language Models (LLMs) have significantly redefined the field of artificial intelligence (AI), enabling machines to understand and generate human-like text with remarkable ...