方法对比

	Agent-Based Sensitivity Analysis	基于主体的建模（ABM）
领域	仿真	仿真
方法族	Process / pipeline	Process / pipeline
起源年份	2000s–2010s	1970s–1990s (formalized as a field)
提出者	Adapted from global sensitivity analysis (Saltelli et al.) for agent-based models	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
类型	Simulation-based sensitivity analysis	Computational simulation method
开创性文献	Saltelli, A., Tarantola, S., Campolongo, F., & Ratto, M. (2004). Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models. John Wiley & Sons. ISBN: 9780470870938	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.
别名	ABM sensitivity analysis, ABSA, SA for ABMs, agent-based model sensitivity testing	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
相关	3	5
摘要	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.	Agent-based modeling (ABM) is a computational simulation method, formalized through the work of Thomas Schelling and Robert Axelrod in the 1970s–1990s, that simulates the behavior of complex systems by specifying and running autonomous agents — individuals, firms, cells, or any bounded entity — whose local interactions with each other and with their environment collectively produce global, system-level patterns that could not be predicted from any single agent's rules alone.