Empirical characterisation of agent behaviours in socio-ecological systems

Agent-based modelling has become an important tool to investigate socio-ecological processes. Its use is partially driven by increasing demand from decision makers to provide support for understanding the potential implications of decisions in complex situations. While one of the advantages of agent-based modelling is the ability to simulate the implications of human decision-making processes explicitly, methods for providing empirical support for the representation of the behaviour of human agents have not been structured systematically. This paper develops a framework for the parameterisation of human behaviour in agent-based models and develops twelve distinct sequences for the characterisation and parameterisation of human behaviours. Examples are provided to illustrate the most important sequences. This framework is a first step towards a guide for parameterisation of human behaviour in ABM. A structured discussion within the agent-based community is needed to achieve a more definitive guideline.

[1]  Marco G A Huigen,et al.  First principles of the MameLuke multi-actor modelling framework for land use change, illustrated with a Philippine case study. , 2004, Journal of environmental management.

[2]  Roger M. Cooke,et al.  TU Delft expert judgment data base , 2008, Reliab. Eng. Syst. Saf..

[3]  Paul L. Nichols,et al.  Social Survey Methods: A field guide for development workers , 1991 .

[4]  Jeremy Mennis,et al.  Intelligent Dasymetric Mapping and Its Application to Areal Interpolation , 2006 .

[5]  Birgit Müller,et al.  A standard protocol for describing individual-based and agent-based models , 2006 .

[6]  Daniel G. Brown,et al.  Illustrating a new conceptual design pattern for agent-based models of land use via five case studies—the MR POTATOHEAD framework , 2008 .

[7]  A. Bregt,et al.  Effects of farmers' decisions on the landscape structure of a Dutch rural region: An agent-based approach , 2010 .

[8]  K. Overmars,et al.  Research, part of a Special Feature on Empirical based agent-based modeling Multiactor Modeling of Settling Decisions and Behavior in the San Mariano Watershed, the Philippines: a First Application with the MameLuke Framework , 2006 .

[9]  Steven M. Manson,et al.  Case studies, cross-site comparisons, and the challenge of generalization: comparing agent-based models of land-use change in frontier regions , 2008, Journal of land use science.

[10]  Philip Rees,et al.  The census data system , 2002 .

[11]  Anna Straton,et al.  Simulating impacts of water trading in an institutional perspective , 2009, Environ. Model. Softw..

[12]  Arnold K. Bregt,et al.  A method to define a typology for agent-based analysis in regional land-use research , 2008 .

[13]  Daniel G. Brown,et al.  Variations in development of exurban residential landscapes: timing, location, and driving forces , 2011 .

[14]  G. Harrison,et al.  Field experiments , 1924, The Journal of Agricultural Science.

[15]  Daniel G. Brown,et al.  Effects of Heterogeneity in Residential Preferences on an Agent-Based Model of Urban Sprawl , 2006 .

[16]  J. Gareth Polhill,et al.  The ODD protocol: A review and first update , 2010, Ecological Modelling.

[17]  Daniel G. Brown,et al.  Evaluating the effects of land‐use development policies on ex‐urban forest cover: An integrated agent‐based GIS approach , 2009, Int. J. Geogr. Inf. Sci..

[18]  François Bousquet,et al.  Dealing with Power Games in a Companion Modelling Process: Lessons from Community Water Management in Thailand Highlands , 2010 .

[19]  Daniel G. Brown,et al.  Survival Analysis in Land Change Science: Integrating with GIScience to Address Temporal Complexities , 2008 .

[20]  Patrick D'Aquino,et al.  The AtollGame Experience: from Knowledge Engineering to a Computer-Assisted Role Playing Game , 2006, J. Artif. Soc. Soc. Simul..

[21]  Thomas Berger,et al.  Research, part of a Special Feature on Empirical based agent-based modeling Creating Agents and Landscapes for Multiagent Systems from Random Samples , 2006 .

[22]  Kirk Hallahan.  Experiment-research methodology in marketing types and applications , 1997 .

[23]  François Bousquet,et al.  Agent-based simulations of interactions between duck population, farming decisions and leasing of hunting rights in the Camargue (Southern France) , 2003 .

[24]  Arnold K. Bregt,et al.  An agent-based approach to model land-use change at a regional scale , 2010, Landscape Ecology.

[25]  Guy Trébuil,et al.  Systems diagnoses at field, farm and watershed levels in diversifying upland agroecosystems: towards comprehensive solutions to farmers’ problems , 1997 .

[26]  J. B. Dent,et al.  Applications of Systems Approaches at the Farm and Regional Levels Volume 1 , 1997, Systems Approaches for Sustainable Agricultural Development.

[27]  Victor Jupp,et al.  The SAGE Dictionary of Social Research Methods , 2006 .

[28]  Scott Moss,et al.  Alternative Approaches to the Empirical Validation of Agent-Based Models , 2007, J. Artif. Soc. Soc. Simul..

[29]  E. Ostrom,et al.  Empirically Based, Agent-based models , 2006 .

[30]  Suzana Dragicevic.  GeoComputation: Modeling with spatial agents , 2008, Comput. Environ. Urban Syst..

[31]  James R.A. Butler,et al.  Implications of ecological data constraints for integrated policy and livelihoods modelling: An example from East Kalimantan, Indonesia , 2011 .

[32]  Mark H. Birkin,et al.  A spatial microsimulation model with student agents , 2008, Comput. Environ. Urban Syst..

[33]  Steven D. Prager,et al.  Disaggregating human population for improved land use management in Kenya , 2010 .

[34]  Uta Berger,et al.  Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology , 2005, Science.

[35]  Nicholas Mark Gotts,et al.  Comparison of empirical methods for building agent-based models in land use science , 2007 .

[36]  M. Janssen,et al.  Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review , 2003 .

[37]  S. Page,et al.  The emergence of zoning policy games in exurban jurisdictions: Informing collective action theory , 2009 .

[38]  William Rand,et al.  Exurbia from the bottom-up: Confronting empirical challenges to characterizing a complex system , 2008 .

[39]  J. Gareth Polhill,et al.  Agent-based land-use models: a review of applications , 2007, Landscape Ecology.

[40]  P. Rousseeuw.  Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[41]  L. C. Dunga,et al.  Facilitating dialogue between aquaculture and agriculture: lessons from role-playing games with farmers in the Mekong Delta, Vietnam , 2009 .

[42]  Olivier Barreteau,et al.  The joint use of role-playing games and models regarding negotiation processes: characterization of associations , 2003, J. Artif. Soc. Soc. Simul..

[43]  G. Kaplan.  What's wrong with social epidemiology, and how can we make it better? , 2004, Epidemiologic reviews.