Social interaction increases the importance of timing, since small changes can have social meaning (e.g., synchronization both results from and reinforces rapport). A core algorithmic challenge I address in my work is how to integrate socially appropriate behavior into temporal models for planning and control algorithms.
My work allows robots to influence, understand, and learn from people in groups, while making minimal assumptions about the specifics of their behavior. My goal is to enable robots to appropriately interact with and learn from people in public spaces, with learning algorithms that appropriately integrate information from diverse users and control algorithms that appropriately respond to human behavior in noisy environments.
Agency is the degree to which something or someone can be considered to have free will and autonomy. A robot's appearance of agency depends on both its behavior and the specific person with whom it is interacting. My work in this area contributed to our understanding of how a robot can predict and influence people's perceptions of its agency.
Elaine Schaertl Short
c/o ECE Department
EER 6.804, C0806
Austin, TX 78712