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DNative-Twin: Decision Graphs and Digital Twins for Reconstructable Agentic Decisions

arXiv · AI, language, vision and robotics · article · Sep 3, 2026 · UTC

AI agents increasingly gather evidence, invoke tools, apply constraints, and produce decisions that people or software may commit to action. A final output alone cannot show which evidence, tool state, rule, authorization, or action path produced it. We present DNative-Twin, a graph-native digital twin that records a committed agentic decision as a typed trajectory and re-executes its decision mechanism under declared conditions. The graph links the state observed by the agent, the path it followed, and the authority behind the resulting action. The twin synchronizes this information, replays

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