Abstract: Autonomy in a multi-robot system refers to the ability to make decisions and perform tasks independently. To be successful, robots must be equipped with adequate sensors to gather data and actuators, so they can make decisions accordingly. But this is not enough. There is the potential for some team members not to be cooperative. They could simply be lazy, or slow at doing their work, perhaps due to battery problems or sensor failures, but they could also intentionally disrupt the work of the team. How can those undesirable behaviors be detected? Recognition of potential issues and adaptation are necessary, especially for critical and time sensitive tasks. We propose to measure trust using a model of trust that has been proposed in the agents’ community and present preliminary results.

Short Bio: Maria Gini is a Distinguished Professor at the University of Minnesota, where her research over the last 40 years has focused on autonomous agents’ decision-making for task allocation, robot exploration of unknown environments, swarm robotics, and teamwork. She is an ACM, AAAI, and IEEE fellow. She received the IJCAI Donald E. Walker Distinguished Service award (2024), ACM/SIGAI Autonomous Agents Research Award (2022), and the Computing Research Association A Nico Habermann Award (2019). She was recently awarded the Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring (PAESMEM).