Avatar-based Macroeconomics - Experimental Insights into Artificial Agents Behavior

Gianfranco Giulioni, Edgardo Bucciarelli, Marcello Silvestri, Paola D'Orazio


In this paper we present a new methodological approach based on the interplay between Experimental Economics and Agent-based Economics. Advances in the design and implementation of individual autonomous economic agents are presented. The methodology is organized in three steps. The first step focuses on agents. We use an inductive rather than a deductive approach: by means of the experimental method we observe agents’ behaviors. The second step is the behavioral rules’ building process that allows us to study how to estimate and structure artificial agents. In the third step, the set of previously induced behavioral rules are used to build artificial agents, i.e. “molded” avatars, which operate in the “archetype” macroeconomic system. The resulting Multi-agent system serves as the macroeconomic environment for our simulations and economic policy analysis.


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Paper Citation

in Harvard Style

Giulioni G., Bucciarelli E., Silvestri M. and D'Orazio P. (2014). Avatar-based Macroeconomics - Experimental Insights into Artificial Agents Behavior . In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-016-1, pages 272-277. DOI: 10.5220/0004917902720277

in Bibtex Style

author={Gianfranco Giulioni and Edgardo Bucciarelli and Marcello Silvestri and Paola D'Orazio},
title={Avatar-based Macroeconomics - Experimental Insights into Artificial Agents Behavior},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},

in EndNote Style

JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Avatar-based Macroeconomics - Experimental Insights into Artificial Agents Behavior
SN - 978-989-758-016-1
AU - Giulioni G.
AU - Bucciarelli E.
AU - Silvestri M.
AU - D'Orazio P.
PY - 2014
SP - 272
EP - 277
DO - 10.5220/0004917902720277