Modelling Evolving Rules for the Use of Common-pool Resources in an Agent-based Model
Institutional arrangements are key drivers of the use of common-pool resources (CPR). The analysis of existing arrangements requires a framework that allows research to describe a case study systematically and diagnose the institutional setting. Based on a sound understanding of current institutions...
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Croatian Interdisciplinary Society
2007-10-01
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Series: | Interdisciplinary Description of Complex Systems |
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Online Access: | http://indecs.eu/2007/indecs2007-pp56-80.pdf |
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doaj-931d0f5285ae48a79ea87f76d6de23762020-11-24T23:38:53ZengCroatian Interdisciplinary SocietyInterdisciplinary Description of Complex Systems1334-46841334-46762007-10-01525680Modelling Evolving Rules for the Use of Common-pool Resources in an Agent-based ModelAlexander SmajglInstitutional arrangements are key drivers of the use of common-pool resources (CPR). The analysis of existing arrangements requires a framework that allows research to describe a case study systematically and diagnose the institutional setting. Based on a sound understanding of current institutions the question of what effects alternate arrangements would have becomes evident. This step requires a predictive model, which can either be qualitative or, preferably, analyses an empirical case quantitatively. A major conceptual challenge of a quantitative model is the evolution of rules, which define the boundaries for the agents to choose strategies. This paper develops the conceptual foundations for such a modelling approach and an agent-based model for the analysis of institutional arrangements in a CPR setting.http://indecs.eu/2007/indecs2007-pp56-80.pdfmulti-agent simulationagent-based modellinginstitutional arrangementscommon-pool resources |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alexander Smajgl |
spellingShingle |
Alexander Smajgl Modelling Evolving Rules for the Use of Common-pool Resources in an Agent-based Model Interdisciplinary Description of Complex Systems multi-agent simulation agent-based modelling institutional arrangements common-pool resources |
author_facet |
Alexander Smajgl |
author_sort |
Alexander Smajgl |
title |
Modelling Evolving Rules for the Use of Common-pool Resources in an Agent-based Model |
title_short |
Modelling Evolving Rules for the Use of Common-pool Resources in an Agent-based Model |
title_full |
Modelling Evolving Rules for the Use of Common-pool Resources in an Agent-based Model |
title_fullStr |
Modelling Evolving Rules for the Use of Common-pool Resources in an Agent-based Model |
title_full_unstemmed |
Modelling Evolving Rules for the Use of Common-pool Resources in an Agent-based Model |
title_sort |
modelling evolving rules for the use of common-pool resources in an agent-based model |
publisher |
Croatian Interdisciplinary Society |
series |
Interdisciplinary Description of Complex Systems |
issn |
1334-4684 1334-4676 |
publishDate |
2007-10-01 |
description |
Institutional arrangements are key drivers of the use of common-pool resources (CPR). The analysis of existing arrangements requires a framework that allows research to describe a case study systematically and diagnose the institutional setting. Based on a sound understanding of current institutions the question of what effects alternate arrangements would have becomes evident. This step requires a predictive model, which can either be qualitative or, preferably, analyses an empirical case quantitatively. A major conceptual challenge of a quantitative model is the evolution of rules, which define the boundaries for the agents to choose strategies. This paper develops the conceptual foundations for such a modelling approach and an agent-based model for the analysis of institutional arrangements in a CPR setting. |
topic |
multi-agent simulation agent-based modelling institutional arrangements common-pool resources |
url |
http://indecs.eu/2007/indecs2007-pp56-80.pdf |
work_keys_str_mv |
AT alexandersmajgl modellingevolvingrulesfortheuseofcommonpoolresourcesinanagentbasedmodel |
_version_ |
1725515426956312576 |