Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Детерминированное агентное моделирование× | Детерминированная системная динамика× | |
|---|---|---|
| Область | Имитационное моделирование | Имитационное моделирование |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1996 | 1961 |
| Автор метода≠ | Epstein, J. M. & Axtell, R. | Jay W. Forrester |
| Тип≠ | Computational simulation — deterministic rule-based agents | Continuous feedback-loop simulation |
| Основополагающий источник≠ | Epstein, J. M., & Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up. MIT Press. ISBN: 9780262550253 | Forrester, J. W. (1961). Industrial Dynamics. MIT Press, Cambridge, MA. ISBN: 9780262560221 |
| Другие названия | D-ABM, Deterministic ABM, Rule-Based Agent Simulation, Fixed-Rule Agent-Based Model | Deterministic SD, Classical System Dynamics, Continuous Simulation SD, Forrester System Dynamics |
| Связанные≠ | 4 | 5 |
| Сводка≠ | Deterministic Agent-Based Modeling (D-ABM) is a computational simulation approach in which autonomous agents follow fully specified, non-random behavioral rules within a structured environment. Every run with identical initial conditions produces identical outcomes, making the model fully reproducible and transparent for analysis of emergent system behavior without stochastic noise. | Deterministic System Dynamics is the classical form of System Dynamics introduced by Jay Forrester in 1961, using fixed (non-probabilistic) ordinary differential equations to simulate stock-and-flow structures and feedback loops over time. All model parameters and relationships are specified as single-valued constants or deterministic functions, yielding a single trajectory for each simulation run. It is widely used in policy analysis, business strategy, ecology, and public health modeling. |
| ScholarGateНабор данных ↗ |
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