Methoden vergleichen

	Deterministische agentenbasierte Modellierung	Zelluläre Automaten
Fachgebiet	Simulation	Simulation
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1996	1940s–1950s (formalized); 1970 (Conway's Game of Life); 2002 (Wolfram's systematic classification)
Urheber	Epstein, J. M. & Axtell, R.	John von Neumann and Stanislaw Ulam (1940s–1950s); popularized by John Conway (1970) and Stephen Wolfram (1980s–2002)
Typ	Computational simulation — deterministic rule-based agents	Grid-based computational simulation model
Wegweisende Quelle	Epstein, J. M., & Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up. MIT Press. ISBN: 9780262550253	Wolfram, S. (2002). A New Kind of Science. Wolfram Media. ISBN: 978-1579550080
Aliasnamen	D-ABM, Deterministic ABM, Rule-Based Agent Simulation, Fixed-Rule Agent-Based Model	CA, Hücresel Otomat (Cellular Automata), lattice model, grid-based simulation
Verwandt	4	5
Zusammenfassung	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.	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.