Interaction Strategy

Interaction strategy research explores how agents, whether humans, AI models, or robots, interact and influence each other, aiming to understand and optimize these dynamics for improved outcomes. Current research focuses on modeling interactions using various techniques, including deep reinforcement learning, graph neural networks, and diffusion models, applied across diverse domains such as human-computer interaction, social networks, and multi-agent systems. This field is significant for advancing AI safety, improving human-AI collaboration, and designing more effective and user-friendly technologies in various sectors, from healthcare to education.