Agent-based models


Journal Article

Agent-based models (ABMs) provide a methodology to explore systems of interacting, adaptive, diverse, spatially situated actors. Outcomes in ABMs can be equilibrium points, equilibrium distributions, cycles, randomness, or complex patterns; these outcomes are not directly determined by assumptions but instead emerge from the interactions of actors in the model. These behaviors may range from rational and payoff-maximizing strategies to rules that mimic heuristics identified by cognitive science. Agent-based techniques can be applied in isolation to create high-fidelity models and to explore new questions using simple constructions. They can also be used as a complement to deductive techniques. Overall, ABMs offer the potential to advance social sciences and to help us better understand our complex world. Copyright © 2014 by Annual Reviews. All rights reserved.

Full Text

Duke Authors

Cited Authors

  • De Marchi, S; Page, SE

Published Date

  • January 1, 2014

Published In

Volume / Issue

  • 17 /

Start / End Page

  • 1 - 20

International Standard Serial Number (ISSN)

  • 1094-2939

Digital Object Identifier (DOI)

  • 10.1146/annurev-polisci-080812-191558

Citation Source

  • Scopus