The last half decade has seen a steep rise in the number of contributions on safe learning
methods for real-world robotic deployments from both the control and reinforcement learning …

The growth of the construction industry is severely limited by the myriad complex challenges
it faces such as cost and time overruns, health and safety, productivity and labour shortages …

We introduce Voyager, the first LLM-powered embodied lifelong learning agent in Minecraft
that continuously explores the world, acquires diverse skills, and makes novel discoveries …

Interpretability in machine learning (ML) is crucial for high stakes decisions and
troubleshooting. In this work, we provide fundamental principles for interpretable ML, and …

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa,
superhuman proficiency in challenging domains. Recently, AlphaGo became the first …

Deep reinforcement learning has recently seen huge success across multiple areas in the
robotics domain. Owing to the limitations of gathering real-world data, ie, sample inefficiency …

Deep reinforcement learning (RL) has emerged as a promising approach for autonomously
acquiring complex behaviors from low-level sensor observations. Although a large portion of …

Recent years have witnessed significant advances in reinforcement learning (RL), which
has registered tremendous success in solving various sequential decision-making problems …

In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …

Reinforcement Learning (RL) has achieved tremendous success in many complex decision-
making tasks. However, safety concerns are raised during deploying RL in real-world …