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Agent-Based Cellular Automata×Automaty komórkowe stochastyczne×
DziedzinaSymulacjaSymulacja
RodzinaProcess / pipelineProcess / pipeline
Rok powstania1986–19961940s–1980s
TwórcaWolfram, S.; Epstein, J. M. & Axtell, R.von Neumann, J. / Ulam, S. (deterministic CA); probabilistic extension formalized by various authors including Wolfram, S. and Chopard, B.
TypHybrid spatial simulationGrid-based stochastic simulation
Źródło pierwotneWolfram, S. (2002). A New Kind of Science. Wolfram Media, Champaign, IL. ISBN: 978-1579550080Wolfram, S. (2002). A New Kind of Science. Wolfram Media, Champaign, IL. ISBN: 9781579550080
Inne nazwyABCA, CA-ABM, Agent-CA, Hybrid Agent-Cellular AutomatonSCA, Probabilistic Cellular Automata, PCA, Stochastic CA
Pokrewne65
PodsumowanieAgent-Based Cellular Automata (ABCA) is a hybrid simulation framework that integrates the local transition rules of cellular automata with the autonomous behavioral logic of agent-based modeling. Cells in a spatial grid both evolve according to neighborhood rules and host agents that perceive, decide, and act, enabling the study of complex spatial phenomena such as land-use change, disease spread, crowd dynamics, and ecosystem evolution.Stochastic Cellular Automata (SCA) extend classical cellular automata by replacing deterministic transition rules with probabilistic ones, allowing each cell on a grid to change state according to a probability distribution conditioned on its neighborhood. This makes SCA a powerful tool for simulating real-world spatial processes where randomness, noise, and uncertainty govern local interactions — from epidemic spread and forest fires to traffic flow and material diffusion.
ScholarGateZbiór danych
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  1. v1
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  3. PUBLISHED

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ScholarGatePorównaj metody: Agent-based cellular automata · Stochastic Cellular Automata. Pobrano 2026-06-18 z https://scholargate.app/pl/compare