Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Агентное моделирование (АМ)× | Имитационное моделирование дискретных событий (DES)× | |
|---|---|---|
| Область | Имитационное моделирование | Имитационное моделирование |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1970s–1990s (formalized as a field) | 1960s (formalized); modern computational form from 1970s onward |
| Автор метода≠ | Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s) | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| Тип≠ | Computational simulation method | Stochastic process simulation |
| Основополагающий источник≠ | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. DOI ↗ | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 |
| Другие названия≠ | ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| Связанные≠ | 5 | 4 |
| Сводка≠ | 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. | Discrete-Event Simulation (DES) is a computational modeling paradigm in which the state of a system changes only at a countable sequence of points in time — the events. Between events nothing changes, so the simulation clock jumps directly from one event to the next. Formalized through the foundational textbooks of Banks, Carson, Nelson and Nicol and of Law in the 1960s–2000s, DES has become the standard tool for analyzing queuing systems, healthcare patient flows, manufacturing lines, and logistics networks where entities move through resources over time. |
| ScholarGateНабор данных ↗ |
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