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Knexus Research


Trust-Guided Behavior Adaptation Using Case-Based Reasoning

AAAI Conferences

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 necessary 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 estimate its trustworthiness and adapt its behavior accordingly. As behavior adaptation is performed, using case-based reasoning (CBR), information about the adaptation process is stored and used to improve the efficiency of future adaptations.


Adapting Autonomous Behavior Based on an Estimate of an Operator's Trust

AAAI Conferences

Robots can be added to human teams to provide improved capabilities or to perform tasks that humans are unsuited for. However, in order to get the full benefit of the robots the human teammates must use the robots in the appropriate situations. If the humans do not trust the robots, they may underutilize them or disuse them which could result in a failure to achieve team goals. We present a robot that is able to estimate its trustworthiness and adapt its behavior accordingly. This technique helps the robot remain trustworthy even when changes in context, task or teammates are possible.