# Directed Acyclic Graph **Entity class:** Causal And Behavioral-Modeling Layer concept **Directed Acyclic Graph** is a representation in which entities or states are nodes and typed relationships or transitions are edges. The operational value of Directed Acyclic Graph lies in preserving time, provenance, confidence, and alternative explanations. ## Counterterrorism predictive-graph role The page records capability and analytic function. Any claim of a named operational deployment remains subject to the [[wiki/Counterterrorism Predictive Graph Evidence Ladder|evidence ladder]]. The analytic state should distinguish ground truth, observed evidence, inferred state, and predicted state. ## Relationships - **domain router:** [[wiki/Causal Inference|Causal Inference]]. - **ontology neighbors:** [[wiki/Causal Graph|Causal Graph]] and [[wiki/DAG|DAG]]. - **synthesis:** [[wiki/Counterterrorism Predictive Graph|Counterterrorism Predictive Graph]] and [[wiki/Predictive Intelligence Loop|Predictive Intelligence Loop]]. ## Sources - [NIST/SEMATECH — e-Handbook of Statistical Methods (accessed September 23, 2026)](https://www.itl.nist.gov/div898/handbook/) - [Oden Institute — Tan Bui-Thanh research profile (accessed September 23, 2026)](https://oden.utexas.edu/people/directory/Tan-Bui/) **As of:** 2026-09-23