Agent-based sensitivity analysis
Agent-based sensitivity analysis (ABSA) applies sensitivity analysis techniques to agent-based models (ABMs) to determine which input parameters most strongly influence emergent outputs. Because ABMs are stochastic and nonlinear, standard analytical derivatives are unavailable; ABSA uses designed simulation experiments — screening methods, variance-based indices, or regression-based surrogates — to rank parameter importance and guide model calibration and validation.
Rekodi ya chanzo
Nukuu zimehamishwa kwa uhalisi kutoka kwa rekodi ya chanzo cha mbinu. Hakuna uthibitisho wa kiwango cha dai unaodokezwa kutoka kwao.
- Saltelli, A., Tarantola, S., Campolongo, F., & Ratto, M. (2004). Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models. John Wiley & Sons. · ISBN 9780470870938
- ten Broeke, G., van Voorn, G., & Ligtenberg, A. (2016). Which Sensitivity Analysis Method Should I Use for My Agent-Based Model? Journal of Artificial Societies and Social Simulation, 19(1), 5. · DOI 10.18564/jasss.2857
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