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Agent-based modelling. History, essence, future

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  • Hanappi, Hardy

Abstract

The currently fashionable modelling tool agent-based simulation is characterized. The first part concerns the past. It presents a selection of the major intellectual roots from which this new tool emerged. It is important for social scientists, in particular for economists, to see that two relevant impacts came from neighbouring disciplines: biology and network theory. The second part concerns the present of ABM. It aims at highlighting the essential features which are characteristic for an agent-based model. Since there are currently several different opinions on this topic, the one presented here also includes some more epistemologically oriented ideas to support its plausibility. In particular the notion of emergence is scrutinized and extended. This part ends with a short recipe stating how to build an agent-based model. In the last part some ideas on the future of agent based modelling are presented. This part follows the sequence of syntax, semantics, and pragmatics. The syntactic challenges, like operators for pattern recognition, will be meat by a continuing variety of software packages and programming languages tailored to support ABM. The semantic aspect of future agent-based modelling hinges on the close relationship between the tool ABM and its object of investigation, e.g. evolutionary political economy. The need to model institutional change or communication processes will imply adaptive evolution of ABM. The pragmatics of future agent-based modelling are finally characterized as the most demanding – but also as the most influential – element that the new tool will bring about.

Suggested Citation

  • Hanappi, Hardy, 2017. "Agent-based modelling. History, essence, future," MPRA Paper 79331, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:79331
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    References listed on IDEAS

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    1. John Geanakoplos & Robert Axtell & J. Doyne Farmer & Peter Howitt & Benjamin Conlee & Jonathan Goldstein & Matthew Hendrey & Nathan M. Palmer & Chun-Yi Yang, 2012. "Getting at Systemic Risk via an Agent-Based Model of the Housing Market," American Economic Review, American Economic Association, vol. 102(3), pages 53-58, May.
    2. Hanappi, Hardy, 2016. "Capital after Capitalism The evolution of the concept of capital in the light of long-run sustainable reproduction of the species," MPRA Paper 77161, University Library of Munich, Germany.
    3. Arthur, W Brian, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, American Economic Association, vol. 84(2), pages 406-411, May.
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    5. W. Brian Arthur, 1994. "Inductive Reasoning, Bounded Rationality and the Bar Problem," Working Papers 94-03-014, Santa Fe Institute.
    6. Shu-Heng Chan & Shu G. Wang, 2010. "Emergent Complexity in Agent-Based Computational Economics," ASSRU Discussion Papers 1017, ASSRU - Algorithmic Social Science Research Unit.
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    Cited by:

    1. Phillip Anthony O’Hara, 2021. "Objectives of the Review of Evolutionary Political Economy’s ‘Manifesto’ and editorial proposals on world problems, complex systems, historico-institutional and corruption issues," Review of Evolutionary Political Economy, Springer, vol. 2(2), pages 359-387, July.
    2. Hanappi, Hardy, 2020. "Perplexing Complexity Human Modelling and Primacy of the Group as Essence of Complexity," MPRA Paper 98129, University Library of Munich, Germany.
    3. Chareunsy, Andrea K., 2018. "Diffusion of development initiatives in a southern Lao community: An agent based evaluation," Journal of Asian Economics, Elsevier, vol. 54(C), pages 53-68.
    4. Hardy Hanappi, 2020. "Perplexing complexity human modelling and primacy of the group as essence of complexity," Review of Evolutionary Political Economy, Springer, vol. 1(3), pages 397-417, November.

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    More about this item

    Keywords

    Agent-based modelling; economic simulation models;

    JEL classification:

    • B20 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - General
    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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