A Human Behavior Exploration Approach Using LLMs for Cyber-Physical Systems

In the early phases of Cyber-Physical Systems (CPS) development, scoping human behavior plays a significant role, especially when interactions extend beyond expected behavior. Here, it is especially challenging to develop cases that capture the full spectrum of human behavior. Up to now, identifying such behavior of humans remains a task for domain experts. We explore how one can use Large Languages Models (LLMs) in the design phase of systems to provide additional information about human-CPS interaction. Our approach proposes a preliminary ontology describing a hierarchy of types of behavior and relevant CPS components as input for prompt templates. It uses them to generate parts of human behavior descriptions, as well as a canned prompt with one variable about behavior. For demonstration, we take a smart building with a Home Energy System as the use case. An initial user evaluation shows that the behavior descriptions generated with standard and ontology-driven prompts complement each other and are useful when assisting humans. The discovered uncommon behaviors can be used to complete interaction scenarios that eventually result in a more robust CPS implementation.