Template-type: ReDIF-Paper 1.0
Author-Name: Matteo Richiardi
Author-Workplace-Name: Institute for New Economic Thinking and Nuffield College, Oxford, UK; Collegio Carlo Alberto, Moncalieri, Italy
Mathematical Institute, University of Oxford
Author-Email: Matteo.Richiardi@maths.ox.ac.uk
Title: The future of agent-based modelling.
Abstract: In this paper, I elaborate on the role of agent-based (AB) modelling for macroeconomic
research. My main tenet is that the full potential of the AB approach has not been realised yet.
This potential lies in the modular nature of the models, which is bought by abandoning the
straitjacket of rational expectations and embracing an evolutionary perspective. I envisage the
foundation of a Modular Macroeconomic Science, where new models with heterogeneous
interacting agents, endowed with partial information and limited computational ability, can be
created by recombining and extending existing models in a unified computational framework.
This crucially requires the development of appropriate application programming interfaces
(APIs), a set of routines, protocols, and tools which define functionalities internally used by the
simulated agents (e.g. learning algorithms) or used by the agents to interact with other agents
(exchange of information, goods and services) that are independent of their respective
implementations.
Acknowledgements.
X-Classification-JEL: 
X-Keywords: 
Length: 24 pages
Creation-Date: 2015-06-30
Number: 2015-W06
File-URL: http://www.nuffield.ox.ac.uk/economics/papers/2015/ABMfuture-v12.pdf
File-Format: application/pdf
Handle: RePEc:nuf:econwp:1506