Reinforcement Learning

We develop an end-to-end model for learning to follow language instructions with compositional policies. Our model combines large …

A major challenge in reinforcement learning is specifying tasks in a manner that is both interpretable and verifiable. One common …

An introductory talk on reinforcement learning, given online to the IndabaX Uganda community.

Simulators are a fundamental part of training robots to solve complex control and navigation tasks. This is due to the speed and safety …

A major challenge in reinforcement learning is specifying tasks in a manner that is both interpretable and verifiable. One common …

An introductory talk on Monte Carlo methods, given at the Deep Learning Indaba.

In this work, we consider the problem of procedural content generation for video game levels. Prior approaches have relied on …

We propose world value functions (WVFs), a type of goaloriented general value function that represents how to solve not just a given …

In this work, we investigate the properties of data that cause popular representation learning approaches to fail. In particular, we …

Using function approximation to represent a value function is necessary for continuous and high-dimensional state spaces. Linear …