# Simulatable Domain **Entity class:** Scientific-computation concept **Domain:** Simulation / Scientific discovery **Maturity:** Developed ## Definition A simulatable domain is a field in which relevant states, interactions, or outcomes can be represented computationally well enough to support useful prediction, experimentation, or design. ## Mechanism and significance Simulatability is a matter of degree: the practical boundary depends on model fidelity, measurement, scale, compute, and whether decisive variables can be observed and validated. ## Relationships - **Research dossier:** [[research/ASI and RSI Timeline Research Moonshots|ASI and RSI Timeline Research Moonshots]] - **Ontology route:** [[ASI and RSI Timeline Ontology#Scientific Intelligence and Recursive Improvement|Scientific Intelligence and Recursive Improvement]] - **Primary fields:** [[AI for Science]] · [[Scientific Acceleration]] · [[Machine Intelligence]] - **Adjacent concepts:** [[Fixed Point of Recursive Self-Improvement]] · [[Metacognition]] ## Sources and provenance - [[research/ASI and RSI Timeline Research Moonshots|ASI and RSI Timeline Research Moonshots]] — immediate source for this node's role in the broadcast research map. ## Evidence boundary The research dossier establishes why this entity or concept belongs in the Moonshots ontology. Time-sensitive organizational, product, policy, and performance claims should be checked against the linked primary source or a current authoritative source before reuse as settled fact. ## Simple Reminders, Quotations, and Thoughts > Anything science can simulate and verify becomes a domain in which AI can search for solutions. That is why virtual models and simulations will play a crucial part in solving biology. > **— Adapted from Richard Socher**, *MOONSHOTS Live, October 2026* [[reminders/Simulation/AI Can Solve What Science Can Simulate and Verify by Richard Socher|AI Can Solve What Science Can Simulate and Verify by Richard Socher]]