Trust Model

Trust modeling aims to computationally represent and predict trust relationships between entities, particularly in human-AI and multi-agent systems. Current research focuses on developing robust and explainable models, often employing graph neural networks or game-theoretic approaches, to account for factors like user behavior, context, and emotional responses, and to address challenges such as adversarial attacks and dynamic trust changes. These advancements are crucial for improving the safety, reliability, and ethical deployment of AI systems across various applications, from autonomous vehicles to social media platforms and human-robot collaboration.