方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| Agent-Based Scenario Analysis× | 系统动力学× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s–2000s | 1961 |
| 提出者≠ | Axelrod, R.; Schoemaker, P. J. H. (combined lineage) | Jay W. Forrester |
| 类型≠ | Hybrid simulation–scenario method | Continuous simulation / feedback modelling |
| 开创性文献≠ | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. Princeton, NJ. ISBN: 9780691015675 | Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159 |
| 别名 | ABSA, ABM scenario analysis, agent-based scenario planning, scenario-driven ABM | stock-flow modelling, Sistem Dinamiği (Stock-Flow Modelleme), SD modelling, feedback simulation |
| 相关≠ | 4 | 3 |
| 摘要≠ | Agent-based scenario analysis embeds agent-based simulation models inside a structured scenario planning framework. Researchers define two to four contrasting future scenarios, configure agent populations and environmental rules to reflect each scenario's assumptions, run the simulation under each condition, and compare emergent outcomes. This makes it possible to explore how decentralized individual behaviors aggregate into system-level consequences under radically different futures. | System dynamics is a continuous simulation method, developed by Jay W. Forrester at MIT in 1961, that represents a complex system through stocks (accumulations), flows (rates of change), and feedback loops. By expressing these relationships as coupled ordinary differential equations, it reproduces how policies, delays, and nonlinear feedbacks drive system behaviour over time — making it a cornerstone tool in policy analysis, organisational modelling, and sustainability research. |
| ScholarGate数据集 ↗ |
|
|