Computational Approaches for Human-Human and Human-Robot Social Interactions

This collection brings together cutting-edge research on how computers can understand and facilitate social interactions between humans and robots. Drawing from multiple disciplines including computer vision, machine learning, and cognitive science, the articles explore everything from gesture recognition to emotional AI, providing a comprehensive look at how technology is learning to interpret human social cues. The research spans both theoretical frameworks and practical applications, making complex computational concepts accessible to readers interested in the intersection of technology and human behavior.

What makes this compilation particularly valuable is its multi-perspective approach, featuring everything from foundational reviews to original research that pushes current boundaries. Students and researchers in robotics, AI, and human-computer interaction will find this especially relevant, as it captures the current state of a rapidly evolving field where machines are increasingly designed to engage with us socially. The diverse methodologies and applications presented here offer both immediate insights and inspiration for future innovations in creating more natural human-robot partnerships.