পদ্ধতির তুলনা করুন

	জটিল সিমুলেশন মডেলগুলিতে প্যারামিটার প্রভাবের পরিমাণ নির্ধারণ	এজেন্ট-ভিত্তিক মডেলিং (ABM)
ক্ষেত্র	অনুকরণ	অনুকরণ
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	2000s–2010s	1970s–1990s (formalized as a field)
প্রবর্তক	Adapted from global sensitivity analysis (Saltelli et al.) for agent-based models	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
ধরন	Simulation-based sensitivity analysis	Computational simulation method
মৌলিক উৎস	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.
অপর নাম	ABM sensitivity analysis, ABSA, SA for ABMs, agent-based model sensitivity testing	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
সম্পর্কিত	3	5
সারসংক্ষেপ	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.