Building Artificial Economies: From Aggregate Data to Experimental Microstructure. A Methodological Survey

  • Gianfranco GiulioniEmail author
  • Paola D’Orazio
  • Edgardo Bucciarelli
  • Marcello Silvestri
Conference paper
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 676)


This paper suggests a methodological appraisal of the main improvements witnessed by the methodology based on the interplay between Experimental Economics (EE) and Agent-based Computational Economics (ACE) in the last 5–6 years. EE and ACE proved to be “natural allies” in that they complement each other: EE helps ACE in dealing with its “degree of freedom” problem and ACE helps EE in controlling and providing benchmarks for experimental subjects’ behavior. The paper discusses the role Evolutionary Computation plays in this bidirectional relationship.


Genetic Algorithm Artificial Agent Experimental Economic Macroeconomic Model Heterogeneous Agent 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Gianfranco Giulioni
    • 1
    • 2
    Email author
  • Paola D’Orazio
    • 1
    • 2
  • Edgardo Bucciarelli
    • 1
    • 2
  • Marcello Silvestri
    • 1
    • 2
  1. 1.Department of PhilosophicalPedagogical and Economic-Quantitative Sciences, “G. D’Annunzio” UniversityPescaraItaly
  2. 2.Research Group for Experimental Microfoundations of Macroeconomics (GEMM)PescaraItaly

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