Trust-guided behavior adaptation using case-based reasoning

Abstract

The addition of a robot to a team can be difficult if the human teammates do not trust the robot. This can result in underutilization or disuse of the robot, even if the robot has skills or abilities that are nec-essary to achieve team goals or reduce risk. To help a robot integrate itself with a human team, we present an agent algorithm that allows a robot to es-timate its trustworthiness and adapt its behavior ac-cordingly. As behavior adaptation is performed, us-ing case-based reasoning (CBR), information about the adaptation process is stored and used to improve the efficiency of future adaptations. 1