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Deep Surrogate Assisted MAP-Elites for Automated Hearthstone Deckbuilding

We study the problem of efficiently generating high-quality and diverse content in games. Previous work on automated deckbuilding in Hearthstone shows that the quality diversity algorithm MAP-Elites can generate a collection of high-performing decks …

A Simple Approach to Continual Learning by Transferring Skill Parameters

In order to be effective general purpose machines in real world environments, robots not only will need to adapt their existing manipulation skills to new circumstances, they will need to acquire entirely new skills on-the-fly. A great promise of …

Long-Term, in-the-Wild Study of Feedback about Speech Intelligibility for K-12 Students Attending Class via a Telepresence Robot

Telepresence robots offer presence, embodiment, and mobility to remote users, making them promising options for homebound K-12 students. It is difficult, however, for robot operators to know how well they are being heard in remote and noisy classroom …

On the Importance of Environments in Human-Robot Coordination

When studying robots collaborating with humans, much of the focus has been on robot policies that coordinate fluently with human teammates in collaborative tasks. However, less emphasis has been placed on the effect of the environment on coordination …

Towards Exploiting Geometry and Time for Fast Off-Distribution Adaptation in Multi-Task Robot Learning

We explore possible methods for multi-task transfer learning which seek to exploit the shared physical structure of robotics tasks. Specifically, we train policies for a base set of pre-training tasks, then experiment with adapting to new …

Increasing Telepresence Robot Operator Awareness of Speaking Volume Appropriateness: Initial Model Development

Telepresence robots could help homebound students to be physically embodied and socially connected in the classroom. However, most telepresence robots do not provide their operators with information about whether their speaking volume is appropriate …