no code implementations • 13 Jun 2022 • Alexandra Kearney, Anna Koop, Johannes Günther, Patrick M. Pilarski
In computational reinforcement learning, a growing body of work seeks to construct an agent's perception of the world through predictions of future sensations; predictions about environment observations are used as additional input features to enable better goal-directed decision-making.
no code implementations • 22 May 2022 • Esra'a Saleh, John D. Martin, Anna Koop, Arash Pourzarabi, Michael Bowling
We focus our investigations on Dyna-style planning in a prediction setting.
no code implementations • 18 Nov 2021 • Alex Kearney, Anna Koop, Johannes Günther, Patrick M. Pilarski
In computational reinforcement learning, a growing body of work seeks to express an agent's model of the world through predictions about future sensations.
no code implementations • 23 Jan 2020 • Alex Kearney, Anna Koop, Patrick M. Pilarski
Constructing general knowledge by learning task-independent models of the world can help agents solve challenging problems.
no code implementations • NeurIPS 2016 • Kieran Milan, Joel Veness, James Kirkpatrick, Michael Bowling, Anna Koop, Demis Hassabis
We introduce the Forget-me-not Process, an efficient, non-parametric meta-algorithm for online probabilistic sequence prediction for piecewise stationary, repeating sources.