This research explores how heterogeneous AI agents can establish common ground during collaboration. By separating communication and action into distinct decision-making policies, agents can engage in micro-conversations that create shared understanding. The work aims to improve teamwork among diverse robots and support future human-AI collaboration in complex environments.
This PhD defense presents computational approaches to human behavior across two domains. First, a construct-mining pipeline uses open-ended responses, sentence embeddings, debiasing, HDBSCAN clustering, and intrusion validation to derive a data-driven taxonomy of emotion regulation strategies. Second, mixed-methods and classifiers analyze German Twitter, linking counter-speech styles to hate reduction at scale.
