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Using Qualitative Evidence to Enhance an Agent-Based Modelling System for Studying Land Use Change
Author(s) -
Gary Polhill,
LeeAnn Sutherland,
Nicholas M. Gotts
Publication year - 2010
Publication title -
journal of artificial societies and social simulation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.768
H-Index - 59
ISSN - 1460-7425
DOI - 10.18564/jasss.1563
Subject(s) - agent based model , land use, land use change and forestry , land use , computer science , environmental resource management , data science , environmental science , ecology , artificial intelligence , biology
This paper describes and evaluates a process of using qualitative field research data to extend the pre-existing FEARLUS agent-based modelling system through enriching its ontological capabilities, but without a deep level of involvement of the stakeholders in designing the model itself. Use of qualitative research in agent-based models typically involves protracted and expensive interaction with stakeholders; consequently gathering the valuable insights that qualitative methods could provide is not always feasible. At the same time, many researchers advocate building completely new models for each scenario to be studied, violating one of the supposed advantages of the object-oriented programming languages in which many such systems are built: that of code reuse. The process described here uses coded interviews to identify themes suggesting changes to an existing model, the assumptions behind which are then checked with respondents. We find this increases the confidence with which the extended model can be applied to the case study, with a relatively small commitment required on the part of respondents.

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