Show me how to win

Abstract

We present an approach for robot learning from demonstration and communication applied to simple board games like Connect Four. In such games, a visual representation of a winning condition on the board can be converted to an extensive form representation that can then support computation of a winning strategy. We present a robot that can learn simple games from responses to visual questions based on synthesized images, or to verbal questions. We illustrate how reliance on both modalities leads to more efficient learning.