Machine learning has long since become a keystone technology, accelerating science and
applications in a broad range of domains. Consequently, the notion of applying learning …

This book describes how to create robots capable to develop the behavioral and cognitive
skills required to perform a task through machine learning methods. It focuses on model-free …

Existing Deep Learning (DL) frameworks typically do not provide ready-to-use solutions for
robotics, where very specific learning, reasoning, and embodiment problems exist. Their …

We present RoboGen, a generative robotic agent that automatically learns diverse robotic
skills at scale via generative simulation. RoboGen leverages the latest advancements in …

The application of deep learning in robotics leads to very specific problems and research
questions that are typically not addressed by the computer vision and machine learning …

We present RoboHive, a comprehensive software platform and ecosystem for research in
the field of Robot Learning and Embodied Artificial Intelligence. Our platform encompasses …

Despite major progress in Robotics and AI, robots are still basically “zombies” repeatedly
achieving actions and tasks without understanding what they are doing. Deep-Learning AI …

Abstract Machine learning, a cornerstone of intelligent systems, has typically been studied in
the context of specific tasks, including clustering (unsupervised learning), classification …

How could machines learn as efficiently as humans and animals? How could machines
learn to reason and plan? How could machines learn representations of percepts and action …

Versions of the “predictive brain” hypothesis rank among the most promising and the most
conceptually challenging visions ever to emerge from computational and cognitive …