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| Deterministic Cellular Automata× | Monte-Carlo-Simulation× | |
|---|---|---|
| Fachgebiet≠ | Simulation | Entscheidungsfindung |
| Familie≠ | Process / pipeline | MCDM |
| Entstehungsjahr≠ | 1940s–1950s | 1949 |
| Urheber≠ | John von Neumann and Stanislaw Ulam | Metropolis, N., Ulam, S. |
| Typ≠ | Discrete deterministic grid simulation | Robustness wrapper — Monte Carlo uncertainty propagation |
| Wegweisende Quelle≠ | von Neumann, J. (1966). Theory of Self-Reproducing Automata. University of Illinois Press, Urbana, IL. (Edited and completed by A. W. Burks.) link ↗ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Aliasnamen≠ | Deterministic CA, Classical Cellular Automata, Rule-based CA, Finite Automata Grid Model | — |
| Verwandt≠ | 6 | 0 |
| Zusammenfassung≠ | Deterministic Cellular Automata (DCA) is a simulation method that models the evolution of complex systems through a regular grid of cells, each holding a discrete state, updated synchronously at each time step according to a fixed, deterministic rule applied to the cell and its neighbors. The outcome is fully reproducible given the same initial conditions and rule set. | MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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