Economics with heterogeneous interacting agents: a practical guide to agent-based modeling, Edited by Alessandro Caiani, Alberto Russo, Antonio Palestrini, Mauro Gallegati

2017 ◽  
Vol 13 (1) ◽  
pp. 197-200
Author(s):  
Wei-Bin Zhang
2017 ◽  
Vol 55 (2) ◽  
pp. 644-647

Christophre Georges of the Department of Economics, Hamilton College reviews “Economics with Heterogeneous Interacting Agents: A Practical Guide to Agent-Based Modeling,” edited by Alessandro Caiani, Alberto Russo, Antonio Palestrini, and Mauro Gallegati. The Econlit abstract for this book begins: “Text for graduate and PhD students, as well as undergraduates with some knowledge of computers and economics comprises four papers emerging from a workshop on agent-based modeling held by the Dipartimento di Scienze Economiche e Sociali at the Università Politecnica delle Marche. Presents a guide to agent-based models (ABM) and the technicalities that need to be solved in order to evaluate the effect of different rules and their switching.”


Author(s):  
Frank H. Westerhoff

SummaryModels with heterogeneous interacting agents have proven to be quite successful in the past. For instance, such models are able to mimic the dynamics of financial markets quite well. The goal of our paper is to explore whether this approach may offer new insights into the working of certain regulatory policies such as transaction taxes, central bank interventions and trading halts. Although this strand of research is rather novel, we argue that agent-based models may be used as artificial laboratories to improve our understanding of how regulatory policy tools function.


2012 ◽  
Vol 15 (supp02) ◽  
pp. 1250047 ◽  
Author(s):  
DIRK J BEZEMER

Given the economy's complex behavior and sudden transitions as evidenced in the 2007–2008 crisis, agent-based models are widely considered a promising alternative to current macroeconomic research dominated by DSGE models. Their failure is commonly interpreted as a failure to incorporate heterogeneous interacting agents. This paper explains that complex behavior and sudden transitions also arise from the economy's financial structure as reflected in its balance sheets, not just from heterogeneous interacting agents. It introduces "flow-of-funds" or "accounting" models, which were pre eminent in successful anticipations of the recent crisis. In illustration, a simple balance sheet model of the economy is developed to demonstrate that non-linear behavior and sudden transition may arise from the economy's balance sheet structure, even without any micro-foundations. The paper concludes by discussing one recent example of combining flow-of-funds and agent-based models. This appears a promising avenue for future research.


Author(s):  
La´szlo´ Gulya´s ◽  
Ga´bor Szemes ◽  
George Kampis ◽  
Walter de Back

Agent Based Modeling (ABM) is a popular technique for dealing with complex systems. An ABM usually consists of many autonomous, interacting agents, and modelers are interested in the system-level, emergent behavior of these agents. In developing an ABM, scalability is one of most critical factors for validation. Looking for an acceptable solution, parallelization often comes into play. However, writing a parallel version of an ABM simulation is at least as hard as developing the original model, and usually takes an expert of the area. This paper demonstrates our ongoing developments based on the idea that ABMs can be classified on the basis of their interior communication topology. We have developed six reusable parallel simulation schemas that can be instantiated with simulation-specific code using the Java language. Our aim was to give general, domain independent support for ABM modelers, where the parallel piece of code is completely transparent. The hope is that ABM modelers can treat their parallel system in almost the same way as they do the original. The paper details our approach as well as the implementation and, towards the end, shows performance results and how one of the templates works in a GRID system.


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