Human Behavior

Human behavior research aims to understand and model the complexities of human actions and decision-making, leveraging diverse data sources and advanced computational techniques. Current research focuses on using large language models (LLMs), agent-based models (ABMs), and multimodal machine learning to simulate and predict behavior across various contexts, from industrial settings to social interactions and autonomous driving. These efforts are significant for improving human-computer interaction, optimizing organizational efficiency, and enhancing the safety and reliability of autonomous systems, among other applications. The field faces challenges in ensuring the realism, generalizability, and ethical implications of these models.

Papers