Agent-Based ModelsSAGE Publications, 2019 M11 15 - 128 páginas Agent-based simulation has become increasingly popular as a modeling approach in the social sciences because it enables researchers to build models where individual entities and their interactions are directly represented. The Second Edition of Nigel Gilbert′s Agent-Based Models introduces this technique; considers a range of methodological and theoretical issues; shows how to design an agent-based model, with a simple example; offers some practical advice about developing, verifying and validating agent-based models; and finally discusses how to plan an agent-based modelling project, publish the results and apply agent-based modeling to formulate and evaluate social and economic policies. |
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abstract action actors agent-based modeling agent-based simulation agents move Ahrweiler approach Artificial Societies Available Axelrod BDI agents behavior Bousquet bugs button Chapter chromosome classifier system cluster cognitive collectivities complex computational model create Deffuant described discrete event simulation distribution economics environment evolutionary computation example experience extremists firms genetic algorithm geographical geographical information system Gilbert households individual industrial districts innovation networks interactions Izquierdo Journal of Artificial knowledge space labeled learning learning classifier system macrolevel messages Microsimulation multi-agent systems NetLogo norms object-oriented programming objects observed opinion dynamics outcome output parameters population production rule program code Pyka random represent Review role-playing game Schelling model Section segregation sensitivity analysis sheep simulation runs Social Simulation Societies and Social Sociology spatial specific Springer Squazzoni step supply chains system dynamics target theory validation values variables Wilensky