Workshop

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

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

We leverage logical composition in reinforcement learning to create a framework that enables an agent to autonomously determine whether …

The ability to produce novel behaviours from existing skills is an important property of lifelong-learning agents. We build on recent …

We propose a method for autonomously learning an object-centric representation of a highdimensional environment that is suitable for …

We propose a framework for defining a Boolean algebra over the space of tasks. This allows us to formulate new tasks in terms of the …

We present a framework for autonomously learning a portable symbolic representation that describes a collection of low-level continuous …

An important property for lifelong-learning agents is the ability to combine existing skills to solve unseen tasks. In general, …

Monte Carlo Tree Search (MCTS) is a family of directed search algorithms that has gained widespread attention in recent years, with its …