Methoden vergleichen
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| Zelluläre Automaten× | Agentenbasiertes Modellieren (ABM)× | |
|---|---|---|
| Fachgebiet | Simulation | Simulation |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1940s–1950s (formalized); 1970 (Conway's Game of Life); 2002 (Wolfram's systematic classification) | 1970s–1990s (formalized as a field) |
| Urheber≠ | John von Neumann and Stanislaw Ulam (1940s–1950s); popularized by John Conway (1970) and Stephen Wolfram (1980s–2002) | Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s) |
| Typ≠ | Grid-based computational simulation model | Computational simulation method |
| Wegweisende Quelle≠ | Wolfram, S. (2002). A New Kind of Science. Wolfram Media. ISBN: 978-1579550080 | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. DOI ↗ |
| Aliasnamen | CA, Hücresel Otomat (Cellular Automata), lattice model, grid-based simulation | ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling |
| Verwandt | 5 | 5 |
| Zusammenfassung≠ | Cellular automata (CA) is a grid-based computational simulation model, first formalized by John von Neumann and Stanislaw Ulam in the 1940s–1950s and brought to wide attention by John Conway's Game of Life (1970) and Stephen Wolfram's systematic classification (2002), in which a lattice of cells — each holding a finite discrete state — evolves in discrete time steps according to local neighborhood interaction rules, causing complex global patterns to emerge from simple local specifications. | 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. |
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