You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

We introduce a neural architecture for navigation in novel environments. Our proposed
architecture learns to map from first-person views and plans a sequence of actions towards …

Similar to humans, RL agents use interactive learning to successfully obtain satisfactory
decision strategies. However, in many cases, it is desirable to learn directly from …

We introduce a new memory architecture for navigation in previously unseen environments,
inspired by landmark-based navigation in animals. The proposed semi-parametric …

In this paper, we review recent deep learning advances in the context of how they have
been applied to play different types of video games such as first-person shooters, arcade …

We present a micro aerial vehicle (MAV) system, built with inexpensive off-the-shelf
hardware, for autonomously following trails in unstructured, outdoor environments such as …

A critical component to enabling intelligent reasoning in partially observable environments is
memory. Despite this importance, Deep Reinforcement Learning (DRL) agents have so far …

Navigation tasks in photorealistic 3D environments are challenging because they require
perception and effective planning under partial observability. Recent work shows that map …

Long-range indoor navigation requires guiding robots with noisy sensors and controls
through cluttered environments along paths that span a variety of buildings. We achieve this …

Representations are crucial for a robot to learn effective navigation policies. Recent work
has shown that mid-level perceptual abstractions, such as depth estimates or 2D semantic …