Quantify uncertainty with Monte Carlo simulations. Fit distributions to expert judgment, model correlated variables, and generate thousands of scenarios from a few inputs. Agent-based models show how simple individual rules add up to collective patterns that no one chose.
Use cases
- Project cost and schedule risk analysis
- Epidemiological simulation (infection counts, outbreak probabilities)
- Financial risk: portfolio return distributions
- Intelligence analysis: uncertainty quantification in assessments
- Emergence and social influence: testing whether clustering or apparent consensus could arise from weak local preferences or peer-pressure cascades