Validation of Agent-based Approach for Simulating the Conversion to Organic Farming

Validation of Agent-based Approach for Simulating the Conversion to Organic Farming

8 Pages · 2017 · 795 KB · English

Validation of Agent-based Approach for. Simulating the Conversion to Organic. Farming. Črtomir ROZMAN1, Andrej ŠKRABA2, Karmen PAŽEK1, Davorin KOFJAČ2. Background and Purpose: The purpose of this study is to describe the principles of the development of parallel sys- tem-dynamics and 

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235 DOI: 101515/orga20170018 Validation of Agentbased Approach for Simulating the Conversion to Organic Farming Črtomir ROZMAN 1, Andrej ŠKRABA 2, Karmen PAŽEK 1, Davorin KOFJAČ 2 Background and Purpose: The purpose of this study is to describe the principles of the development of parallel sys temdynamics and agentbased models of organic farming for the case of Slovenia The advantage of agentbased modeling is demonstrated by including geospatial information as an agent attribute The models were compared by the validation, confirming the appropriate level of similarity Design/Methodology/Approach: Both systemdynamics and agentbased modeling approaches were applied Statistical methods were used in the validation Results: The results of the validation confirm the appropriateness of the proposed agentbased model Introducing additional attributes into the agentbased model provides an important advantage over the systemdynamics model, which serves as the paradigmatic example Conclusion: A thorough validation and comparison of the results of the systemdynamics and agentbased models indicates the proper approach to combining the methodologies This approach is promising, because it enables the modeling of the entire agricultural sector, taking each particular farm into account Keywords: agentbased models; organic farming; system dynamics; validation; multimethod simulation 1 University of Maribor, Faculty of Agriculture and Life Sciences, Pivola 11, 2311 Hoče, Slovenia [email protected], [email protected] 2 University of Maribor, Faculty of Organizational Sciences, Kidričeva cesta 55a, 4000 Kranj, Slovenia [email protected], [email protected] 1 Received: February 6, 2017; revised: March 12, 2017; accepted: April 15, 2017 1 Introduction Organic farming has been declared the most viable farming system in terms of sustainability (Rozman et al, 2013) and has been modeled by various approaches (Rozman et al, 2015) The systemdynamics (SD) methodology has been applied by Shi and Gill (2005) for the modeling of ecolog ical agriculture development for Jinshan County (China) and by Rozman et al (2013) for the modeling the develop ment of organic agriculture in Slovenia Agentbased mod eling (ABM) has emerged as an alternative approach that has become possible with the increased computing power of personal computers Agentbased modeling is the com putational study of social agents as evolving systems of autonomous, interacting agents from the complex adaptive system perspective ABM researchers are interested in how macro phenomena emerge from microlevel behavior among a heterogeneous set of interacting agents (Holland, 1992) By using ABM as computational laboratories, one may test in a systematic way different hypotheses related to at tributes of the agents, their behavioral rules, the types of interactions, and their effect on stylized macrolevel facts of the system (Jansen, 2005) In designing an ABM, the modeler takes a “bottomup” approach by considering the relevant actors and decisions at the micro level that may produce an observable macro phenomenon (eg, a systemlevel outcome) Therefore, the use of ABM to im prove our understanding or support the rigorous analysis of potential outcomes of that system (eg, scenario and policy analysis) requires that ABMs have credible and de fensible representations of microprocesses This require Unauthenticated Download Date | 6/29/19 8:24 AM Organizacija, Volume 50 Number 3, August 2017 Research Papers 236 ment raises important questions about available empirical approaches for capturing micro processes and their rel ative merits (Robinson et al, 2007) Gaube et al (2009) used ABM in combination with stockandflow models for participative analysis of landuse systems in Reichraming (Austria) In this light, Deffuant et al (2002) presented agentbased simulation of organicfarming conversion in Allier département, where they combined mixedmethods research with integrated ABM to explain land change and economic decisionmaking in the United States and Mex ico In this paper, we present the development of an agent based model for conversion to organic farming and com pare it to an SD conversion model The model will con sider only the structure of information spread, ie market absorption We have developed a parallel model, in which the main parameters

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