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The future of agent-based modelling

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  • Matteo Richiardi

    () (Institute for New Economic Thinking and Nuffield College, Oxford, UK; Collegio Carlo Alberto, Moncalieri, Italy Mathematical Institute, University of Oxford)

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.

Suggested Citation

  • Matteo Richiardi, 2015. "The future of agent-based modelling," Economics Papers 2015-W06, Economics Group, Nuffield College, University of Oxford.
  • Handle: RePEc:nuf:econwp:1506
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