LAMDA: Large Language Model as Decision Analyst
Published in: Decision Analysis, 2026
LAMDA uses large language models to convert unstructured natural-language descriptions of decision problems into draft influence diagrams. The framework combines graph generation and probability elicitation with rule-based verification and iterative regeneration to resolve structural and formatting issues. The study evaluates LAMDA on a dataset of typical decision problems under risk and applies it to expert group discussions about a hypothetical pandemic. The resulting diagrams organize decision-relevant variables, relationships, beliefs, and preferences for human review and refinement, supporting decision analysts in information processing and decision-making.
Recommended Citation: Hong, Y., Qin, S.Z., Wang, C., 2026. LAMDA: Large Language Model as Decision Analyst. Decision Analysis, Articles in Advance. https://doi.org/10.1287/deca.2025.0438
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