Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Агентний аналіз сценаріїв× | Агентне моделювання (ABM)× | |
|---|---|---|
| Галузь | Імітаційне моделювання | Імітаційне моделювання |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1990s–2000s | 1970s–1990s (formalized as a field) |
| Автор методу≠ | Axelrod, R.; Schoemaker, P. J. H. (combined lineage) | Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s) |
| Тип≠ | Hybrid simulation–scenario method | Computational simulation method |
| Основоположне джерело≠ | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. Princeton, NJ. ISBN: 9780691015675 | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. DOI ↗ |
| Інші назви | ABSA, ABM scenario analysis, agent-based scenario planning, scenario-driven ABM | ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling |
| Пов'язані≠ | 4 | 5 |
| Підсумок≠ | 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. | 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. |
| ScholarGateНабір даних ↗ |
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