Agents
The extraction of a small number of relevant insights from vast amounts of data is a crucial component of data-driven decision-making. …
In this work, we investigate the challenges associated with developing goal-driven AI agents capable of performing open-ended tasks in …
Handling out-of-distribution (OOD) samples has become a major stake in the real-world deploy- ment of machine learning systems. This …
Unsupervised skill learning aims to learn a rich repertoire of behaviors without external supervision, providing artificial agents with …
Robots in many real-world settings have access to force/torque sensors in their gripper and tactile sensing is often necessary in tasks …
The ALFRED environment features an embodied agent following instructions and accomplishing tasks in simulated home environments. …
Different types of mental rotation tests have been used extensively in psychology to understand human visual reasoning and perception. …
As deep reinforcement learning driven by visual perception becomes more widely used there is a growing need to better understand and …