Reinforcement Learning

An agent tasked with solving a number of different decision making problems in similar environments has an opportunity to learn over a …

This paper addresses the problem of online decision making in continually changing and complex environments, with inherent …

An agent continuously performing different tasks in the same domain has the opportunity to learn, over the course of its operational …

Representation learning is a difficult and important problem for autonomous agents. This paper presents an approach to automatic …

Interactive interfaces are a common feature of many systems ranging from field robotics to video games. In most applications, these …

This paper considers the problem of providing advice to an autonomous agent when neither the behavioural policy nor the goals of that …

The computational complexity of learning in sequential decision problems grows exponentially with the number of actions available to …

Constructing robust controllers to perform tasks in large, continually changing worlds is a difficult problem. A long-lived agent …

Although a manipulator must interact with objects in terms of their full complexity, it is the qualitative structure of the objects in …

This paper addresses the problem of acquiring a hierarchically structured robotic skill in a non-stationary environment. This is …