University of Pennsylvania researchers tweaked an AI tutor to tailor the difficulty of practice problems for each student.

Robust Reinforcement Learning-based model for UAV self-separation under Uncertainty. Hybrid; Amsterdam , Noord-Holland , Netherlands; Aerosp ...

Reinforcement learning has become the central approach for language models (LMs) to learn from environmental reward or feedback. In practice, the environmental feedback is usually sparse and delayed.

Study authors Hunter Schweiger (left) and Ash Robbins. Imagine balancing a ruler vertically in the palm of your hand: you have to constantly pay attention to the angle of the ruler and make many small ...

Leaders, whether in boardrooms or garages, constantly face an unchanging force: uncertainty. For a CEO, making a good decision always involves factoring in as much data as possible, and then trusting ...

Over the past few years, AI systems have become much better at discerning images, generating language, and performing tasks within physical and virtual environments. Yet they still fail in ways that ...

Every year, NeurIPS produces hundreds of impressive papers, and a handful that subtly reset how practitioners think about scaling, evaluation and system design. In 2025, the most consequential works ...

Watch an AI agent learn how to balance a stick—completely from scratch—using reinforcement learning! This project walks you through how an algorithm interacts with an environment, learns through trial ...

This is a fork of "RL-ViGen: A Reinforcement Learning Benchmark for Visual Generalization" to make it more portable for ease of use in research. The goal of this repository is to provide an easier way ...