Process / pipeline
Agent-Based Modeling (ABM) — Simulating Emergent Complexity
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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Sources
- Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. DOI: 10.1515/9781400822300 ↗
- Wilensky, U. & Rand, W. (2015). An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo. MIT Press. ISBN: 978-0262731898
Related methods
Referenced by
Agent-based ant colony optimizationAgent-based cellular automataAgent-based Discrete-Event SimulationAgent-based dynamic programmingAgent-based genetic algorithmAgent-based goal programmingAgent-based integer programmingAgent-based Markov modelAgent-based microsimulationAgent-based multi-objective optimizationAgent-based NSGA-IIAgent-based queueing simulationAgent-based scenario analysisAgent-based sensitivity analysisAgent-based system dynamicsAgent-based Tabu SearchBayesian Agent-Based ModelingCA-MarkovCellular AutomataDeterministic Agent-Based ModelingDeterministic Cellular AutomataDeterministic System DynamicsDiscrete-Event SimulationDiscrete-Event System SimulationFuzzy Cognitive MapsMicrosimulationMulti-objective agent-based modelingMulti-objective cellular automataPolicy Scenario Agent-Based ModelingPolicy Scenario Cellular AutomataQueueing SimulationRobust Agent-Based ModelingSelf-Organized CriticalitySimulation-assisted causal-comparative researchSimulation-assisted cross-sectional researchSimulation-assisted ex post facto designSIR ModelStochastic Cellular AutomataStochastic Differential EquationsStochastic Discrete-Event Simulation