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 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.
Cite
Text
Floyd et al. "Trust-Guided Behavior Adaptation Using Case-Based Reasoning." International Joint Conference on Artificial Intelligence, 2015.Markdown
[Floyd et al. "Trust-Guided Behavior Adaptation Using Case-Based Reasoning." International Joint Conference on Artificial Intelligence, 2015.](https://mlanthology.org/ijcai/2015/floyd2015ijcai-trust/)BibTeX
@inproceedings{floyd2015ijcai-trust,
title = {{Trust-Guided Behavior Adaptation Using Case-Based Reasoning}},
author = {Floyd, Michael W. and Drinkwater, Michael and Aha, David W.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2015},
pages = {4261-4267},
url = {https://mlanthology.org/ijcai/2015/floyd2015ijcai-trust/}
}