Implicit Communication

Implicit communication, the conveyance of information through indirect cues like gaze, facial expressions, and subtle movements, is a burgeoning research area focusing on improving human-robot interaction (HRI) and understanding how humans and machines infer meaning from non-verbal signals. Current research explores methods like active shadowing to manipulate perceptions, leveraging transfer entropy to modulate influence in collaborative or competitive scenarios, and employing contextual bandit algorithms in federated learning settings to learn from implicit user feedback. These advancements hold significant potential for enhancing the naturalness, efficiency, and acceptance of human-machine interactions across diverse applications, from robotics and virtual agents to personalized language models.