HAG: Hierarchical Demographic Tree-based Agent Generation for Topic-Adaptive Simulation

1. 1Identify the topic or domain for simulation
2. 2Construct a hierarchical demographic tree to capture macro-level joint distributions
3. 3Generate agents using the tree-based approach to ensure micro-level individual rationality
4. 4Evaluate and refine the generated agents for topic-adaptive simulation

AI engineers and researchers working on agent-based modeling and simulation can benefit from HAG, as it provides a robust framework for generating high-fidelity agents that adapt to diverse topics and domains

💡 HAG combines the strengths of static data-based retrieval and LLM-based generation methods to create a robust and adaptive agent generation framework

🤖 HAG: a novel framework for topic-adaptive agent generation in simulation #AI #AgentBasedModeling