Sustainability analysis represents a form of Complex Adaptive Systems (CAS) because it involves multiple sectors and agents displaying non-linear and non-rational interacting behaviours characterized by feedbacks and time lags. Thus, it cannot be properly addressed with classical econometric models such as General Equilibrium Models (GEM), nor with traditional simulation models alone including System Dynamics (SD), Dynamic Systems (DS), Discrete Event Simulation (DES), Agent Based Models (ABM). We present a hybrid SD-ABM approach and argue that this may potentially better address such issues in a more informative and effective way because they exploit the strengths of both of these forms of models. In particular, we describe how this emerging modelling framework can contribute to understanding complex systems, increasing modelling accuracy and computational efficiency. Then, we highlight the methodological challenges of SD-ABM integration. Among the relevant applications, this new modelling approach would aid the understanding of the characteristics and evolution of the resources-economic growth-population nexus. There is an increasing need to research this nexus to help define the processes involved in the changes in prices of global commodities like oil and cereals since middle of the last decade which has partly been driven by a supply-demand mismatch. The SD-ABM hybrid model framework presented here will contribute to the wider development and refinement of hybrid models for sustainability analysis which will provide policy makers with meaningful and timely results on alternative policy scenarios in order to allow them to introduce more targeted low carbon, resource resilient environmental sustainability policies.

A hybrid System Dynamics – Agent Based model to simulate Complex Adaptive Systems: a new methodological framework for sustainability analysis.

TONELLI, FLAVIO;
2014-01-01

Abstract

Sustainability analysis represents a form of Complex Adaptive Systems (CAS) because it involves multiple sectors and agents displaying non-linear and non-rational interacting behaviours characterized by feedbacks and time lags. Thus, it cannot be properly addressed with classical econometric models such as General Equilibrium Models (GEM), nor with traditional simulation models alone including System Dynamics (SD), Dynamic Systems (DS), Discrete Event Simulation (DES), Agent Based Models (ABM). We present a hybrid SD-ABM approach and argue that this may potentially better address such issues in a more informative and effective way because they exploit the strengths of both of these forms of models. In particular, we describe how this emerging modelling framework can contribute to understanding complex systems, increasing modelling accuracy and computational efficiency. Then, we highlight the methodological challenges of SD-ABM integration. Among the relevant applications, this new modelling approach would aid the understanding of the characteristics and evolution of the resources-economic growth-population nexus. There is an increasing need to research this nexus to help define the processes involved in the changes in prices of global commodities like oil and cereals since middle of the last decade which has partly been driven by a supply-demand mismatch. The SD-ABM hybrid model framework presented here will contribute to the wider development and refinement of hybrid models for sustainability analysis which will provide policy makers with meaningful and timely results on alternative policy scenarios in order to allow them to introduce more targeted low carbon, resource resilient environmental sustainability policies.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/751395
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