After helping build some of the world's most widely used open AI datasets at Hugging Face, Guilherme Penedo and Hynek ...

This paper proposes an exploration-efficient deep reinforcement learning with reference (DRLR) policy framework for learning robotics tasks incorporating demonstrations. The DRLR framework is ...

Most robot headlines follow a familiar script: a machine masters one narrow trick in a controlled lab, then comes the bold promise that everything is about to change. I usually tune those stories out.

Quantum phase estimation (QPE) is a foundational algorithm for quantum chemistry, cryptanalysis, and solving linear equations, due to the potential of exponential acceleration for classical algorithms ...

Learning from demonstration is an approach that allows users to personalize a robot’s tasks. While demonstrations often focus on conveying the robot’s motion or task plans, they can also communicate ...

Abstract: Trajectory learning is one of the key components of robot Programming by Demonstration approaches, which in many cases, especially in industrial practice, aim at defining complex ...

Abstract: Learning from demonstration holds the promise of enabling robots to learn diverse actions from expert experience. In contrast to learning from observation-action pairs, humans learn to ...

Although many chemistry demonstrations are proposed in educational literature, there are hardly any studies on how demonstrations should be set up in order to support students’ perception. Against ...

Last year I took a group of students to Cuba to produce documentaries about the island nation's culture and history. The main objective was learning how to produce documentaries, but one of my ...

In an overview of the preparedness of high school seniors for college level work, Kuh (2007) comes to conclusions familiar to many teachers. Most entering students are not adequately prepared either ...