What Should I Know? Using Meta-gradient Descent for Predictive Feature Discovery in a Single Stream of Experience

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.

Continual Learning Decision Making

Temporal-Difference Learning to Assist Human Decision Making during the Control of an Artificial Limb

no code implementations • 18 Sep 2013 • Ann L. Edwards, Alexandra Kearney, Michael Rory Dawson, Richard S. Sutton, Patrick M. Pilarski

In the present work, we explore the use of temporal-difference learning and GVFs to predict when users will switch their control influence between the different motor functions of a robot arm.

Decision Making Reinforcement Learning (RL)