In recent years, the field of robotics has undergone significant transformation, driven increasingly by advances in brain-inspired and neurally grounded ...

For a long time, the core idea in reinforcement learning (RL) was that AI agents should learn every new task from scratch, like a blank slate. This "tabula rasa" approach led to amazing achievements, ...

Abstract: Inverse reinforcement learning optimal control is under the framework of learner–expert, the learner system can learn expert system's trajectory and optimal control policy via a ...

Rated Red goes back to basics with the first steps in learning archery. Pentagon removes key protections for civilian workers, moves to fire with ‘speed and conviction’ Scientists Studied 'SuperAgers' ...

Abstract: This paper proposes a hierarchical safe reinforcement learning with prescribed performance control (HSRL-PPC) scheme to address the challenges of interconnected leader-follower systems ...

By teaching models to reason during foundational training, the verifier-free method aims to reduce logical errors and boost ...

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 ...

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 ...