In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...

In reinforcement learning (RL), an agent learns to achieve its goal by interacting with its environment and learning from feedback about its successes and failures. This feedback is typically encoded ...

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 ...

This beginner-friendly tutorial shows how to create clear, interactive graphs in GlowScript VPython. You’ll learn the basics of setting up plots, graphing data in real time, and customizing axes and ...

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 ...

DR Tulu-8B is the first open Deep Research (DR) model trained for long-form DR tasks. DR Tulu-8B matches OpenAI DR on long-form DR benchmarks. Feburary 9, 2026: 🔥 We released a free interactive demo ...

The rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for ...

Thinking about learning Python? It’s a pretty popular language these days, and for good reason. It’s not super complicated, which is nice if you’re just starting out. We’ve put together a guide that ...

We investigate Reinforcement Learning (RL) on Agentic search tasks without explicit gathering information from external search engines, e.g., LLMs, web engines. Previous work leverage external search ...

Nearly a century ago, psychologist B.F. Skinner pioneered a controversial school of thought, behaviorism, to explain human and animal behavior. Behaviorism directly inspired modern reinforcement ...