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COMPLEX AGENT-BASED MODELS: APPLICATION OF A CONSTRUCTIVISM IN THE ECONOMIC RESEARCH

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COMPLEX AGENT-BASED MODELS: APPLICATION OF A CONSTRUCTIVISM IN THE ECONOMIC RESEARCH

Name and surname of author:

Vladimír Bureš, Petr Tučník

Year:
2014
Volume:
17
Issue:
3
Keywords:
Multi-agent modelling, agent-based computational economics, NetLogo, resource
DOI (& full text):
http://dx.doi.org/10.15240/tul/001/2014-3-012
Anotation:
The current state in research of economic systems is characterised by two prevailing issues. Firstly, study of economic systems is traditionally based on analytical and econometric tools, which have been the main arbiters of the veracity or plausibility of assumptions and hypotheses in economics. This approach has been proved to be highly suitable for theory development. Secondly, practical issues and necessity to support decision-making led to development of various modelling and simulation techniques or tools. However, majority of these approaches usually fail when coping with complexity. Furthermore, several main areas of interest can be identified in the business and economics modelling. Nevertheless, these areas are mostly independent due to their problembased focusing on particular issues and their solutions. Depicted gaps might be bridged with the help of new modelling paradigms that have been established only recently. Application of agentbased modelling in the realm of economic systems is labelled as Agent-based Computational Economics (ACE). In particular sections of this paper results of experiments run on the novel model are described. The model is based on agents, which are described as a vector of several observed parameters, and four types of agents are used, namely consumer agent, factory agent, mining agent, and transportation agent. In addition, a colony is added as the fifth type of meta-agent. Scalability and configuration options of the model enable for various configuration and thus for conducting specific experiments. The presented system is already implemented as a prototype version in the NetLogo environment. The paper depicts two example scenarios, ressource production and resource proximity, and offers interpretation of achieved results. Since most of the work done so far was focused on individual agents, group perspective as an important extensit of ACE modelling is suggested as the further research and development direction.
The current state in research of economic systems is characterised by two prevailing issues. Firstly, study of economic systems is traditionally based on analytical and econometric tools, which have been the main arbiters of the veracity or plausibility of assumptions and hypotheses in economics. This approach has been proved to be highly suitable for theory development. Secondly, practical issues and necessity to support decision-making led to development of various modelling and simulation techniques or tools. However, majority of these approaches usually fail when coping with complexity. Furthermore, several main areas of interest can be identified in the business and economics modelling. Nevertheless, these areas are mostly independent due to their problembased focusing on particular issues and their solutions. Depicted gaps might be bridged with the help of new modelling paradigms that have been established only recently. Application of agentbased modelling in the realm of economic systems is labelled as Agent-based Computational Economics (ACE). In particular sections of this paper results of experiments run on the novel model are described. The model is based on agents, which are described as a vector of several observed parameters, and four types of agents are used, namely consumer agent, factory agent, mining agent, and transportation agent. In addition, a colony is added as the fifth type of meta-agent. Scalability and configuration options of the model enable for various configuration and thus for conducting specific experiments. The presented system is already implemented as a prototype version in the NetLogo environment. The paper depicts two example scenarios, ressource production and resource proximity, and offers interpretation of achieved results. Since most of the work done so far was focused on individual agents, group perspective as an important extensit of ACE modelling is suggested as the further research and development direction.
Section:
Information management
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