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Modelització Basada en Agents (ABM)×Simulació Monte Carlo×
CampSimulacióPresa de decisions
FamíliaProcess / pipelineMCDM
Any d'origen1970s–1990s (formalized as a field)1949
Autor originalThomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)Metropolis, N., Ulam, S.
TipusComputational simulation methodRobustness wrapper — Monte Carlo uncertainty propagation
Font seminalAxelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
ÀliesABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
Relacionats50
ResumAgent-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.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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ScholarGateCompara mètodes: Agent-Based Modeling · MONTE-CARLO-SIMULATION. Recuperat el 2026-06-15 de https://scholargate.app/ca/compare