Ideal, Best, and Emerging Practices in Creating Artificial Societies

Artificial societies used to guide and evaluate policies should be built by following “best practices”. However, this goal may be challenged by the complexity of artificial societies and the interdependence of their sub-systems (e.g., built environment, social norms). We created a list of seven practices based on simulation methods, specific aspects of quantitative individual models, and data-driven modeling. By evaluating published models for public health with respect to these ideal practices, we noted significant gaps between current and ideal practices on key items such as replicability and uncertainty. We outlined opportunities to address such gaps, such as integrative models and advances in the computational machinery used to build simulations.

[1]  Christophe Le Page,et al.  Tools and methods in participatory modeling: Selecting the right tool for the job , 2018, Environ. Model. Softw..

[2]  Philippe J. Giabbanelli,et al.  Should we simulate mental models to assess whether they agree? , 2018, SpringSim.

[3]  Christopher J. Lynch,et al.  Big data, agents, and machine learning: towards a data-driven agent-based modeling approach , 2018, SpringSim.

[4]  Peter Barbrook-Johnson,et al.  Computational Modelling of Public Policy: Reflections on Practice , 2018, J. Artif. Soc. Soc. Simul..

[5]  Claes Andersson,et al.  Wickedness and the anatomy of complexity , 2017 .

[6]  Rik Crutzen,et al.  Using Agent-Based Models to Develop Public Policy about Food Behaviours: Future Directions and Recommendations , 2017, Comput. Math. Methods Medicine.

[7]  Alexey A. Voinov,et al.  An overview of the model integration process: From pre-integration assessment to testing , 2017, Environ. Model. Softw..

[8]  Brian Castellani,et al.  Cases, clusters, densities: Modeling the nonlinear dynamics of complex health trajectories , 2016, Complex..

[9]  Philippe J. Giabbanelli,et al.  A Novel Visualization Environment to Support Modelers in Analyzing Data Generated by Cellular Automata , 2016, HCI.

[10]  Philippe J. Giabbanelli,et al.  Supporting a systems approach to healthy weight interventions in British Columbia by modeling weight and well-being , 2016, SpringSim.

[11]  J. Pagán,et al.  Social Norms and the Consumption of Fruits and Vegetables across New York City Neighborhoods , 2016, Journal of Urban Health.

[12]  R. West Data and statistical commands should be routinely disclosed in order to promote greater transparency and accountability in clinical and behavioral research. , 2016, Journal of clinical epidemiology.

[13]  John P A Ioannidis,et al.  Anticipating consequences of sharing raw data and code and of awarding badges for sharing. , 2016, Journal of clinical epidemiology.

[14]  Forrest Stonedahl,et al.  The Complexities of Agent-Based Modeling Output Analysis , 2015, J. Artif. Soc. Soc. Simul..

[15]  S. D. de Vlas,et al.  Reducing Income Inequalities in Food Consumption: Explorations With an Agent-Based Model. , 2015, American journal of preventive medicine.

[16]  Ross A. Hammond Considerations and Best Practices in Agent-Based Modeling to Inform Policy , 2015 .

[17]  Mikel D. Petty,et al.  A Call to Arms: Standards for Agent-Based Modeling and Simulation , 2015, J. Artif. Soc. Soc. Simul..

[18]  Philippe J. Giabbanelli,et al.  Exploring the Interactions Between Physical Well-Being, and Obesity , 2015 .

[19]  Jun Zhang,et al.  Network interventions on physical activity in an afterschool program: an agent-based social network study. , 2015, American journal of public health.

[20]  Onyebuchi A Arah,et al.  Agent-based modeling of noncommunicable diseases: a systematic review. , 2015, American journal of public health.

[21]  Gnana Bharathy,et al.  A systems approach to healthcare: Agent-based modeling, community mental health, and population well-being , 2015, Artif. Intell. Medicine.

[22]  Hazhir Rahmandad,et al.  Modeling Social Norms and Social Influence in Obesity , 2015, Current Epidemiology Reports.

[23]  Ross A Hammond,et al.  A model of social influence on body mass index , 2014, Annals of the New York Academy of Sciences.

[24]  Claes Andersson,et al.  Societal systems – Complex or worse? , 2014 .

[25]  Takeru Igusa,et al.  Examining social norm impacts on obesity and eating behaviors among US school children based on agent-based model , 2014, BMC Public Health.

[26]  S. Galea,et al.  Reducing racial disparities in obesity: simulating the effects of improved education and social network influence on diet behavior. , 2014, Annals of epidemiology.

[27]  J. Trogdon,et al.  The effect of friend selection on social influences in obesity. , 2014, Economics and human biology.

[28]  O. Wolkenhauer Why model? , 2013, Front. Physiol..

[29]  David Byrne,et al.  Complexity Theory and the Social Sciences : The state of the art , 2013 .

[30]  Abdulrahman M El-Sayed,et al.  Are network-based interventions a useful antiobesity strategy? An application of simulation models for causal inference in epidemiology. , 2013, American journal of epidemiology.

[31]  Sara S. Metcalf,et al.  Agent-based modeling of policies to improve urban food access for low-income populations , 2013 .

[32]  Rik Crutzen,et al.  An Agent-Based Social Network Model of Binge Drinking Among Dutch Adults , 2013, J. Artif. Soc. Soc. Simul..

[33]  Joseph H. A. Guillaume,et al.  Characterising performance of environmental models , 2013, Environ. Model. Softw..

[34]  Jonathan Karnon,et al.  Model Parameter Estimation and Uncertainty: a Report of the Ispor-smdm Modeling Good Research Practices Task Force-6 Background to the Task Forcemodel-parameter-estimation-and- Uncertainty-analysis.asp). a Summary of These Articles Was Pre- Sented at a Plenary Session at the Ispor 16th Annual Intern , 2022 .

[35]  Uwe Siebert,et al.  Modeling good research practices--overview: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--1. , 2012, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[36]  Carson C. Chow,et al.  Quantification of the effect of energy imbalance on bodyweight , 2011, The Lancet.

[37]  Tillal Eldabi,et al.  Development of modelling method selection tool for health services management: From problem structuring methods to modelling and simulation methods , 2011, BMC health services research.

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

[39]  Valerie Spicer,et al.  A cellular automata model on residential migration in response to neighborhood social dynamics , 2010, Math. Comput. Model..

[40]  Jennifer Badham,et al.  A compendium of modelling techniques , 2010 .

[41]  Emily K. Lada,et al.  Multivariate Input Models for Stochastic Simulation , 2005 .

[42]  A. Hill Social and Psychological Factors in Obesity , 2009 .

[43]  M. Petticrew,et al.  Developing and evaluating complex interventions: the new Medical Research Council guidance , 2008, BMJ : British Medical Journal.

[44]  Saltelli Andrea,et al.  Global Sensitivity Analysis: The Primer , 2008 .

[45]  Edgar Morin,et al.  Restricted Complexity, General Complexity , 2006, ArXiv.

[46]  Roger Moore,et al.  An overview of the open modelling interface and environment (the OpenMI) , 2005 .

[47]  David Lane,et al.  Ontological uncertainty and innovation , 2005 .

[48]  Stewart Robinson,et al.  Simulation: The Practice of Model Development and Use , 2004 .

[49]  K. Preston White,et al.  A comparison of five steady-state truncation heuristics for simulation , 2000, 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165).

[50]  L. Epstein,et al.  Treatment of pediatric obesity. , 1998, Pediatrics.

[51]  David J. Pannell,et al.  Sensitivity Analysis of Normative Economic Models: Theoretical Framework and Practical Strategies , 1997 .

[52]  Philippe J. Giabbanelli,et al.  Navigating Complex Systems for Policymaking Using Simple Software Tools , 2018 .

[53]  P. Giabbanelli Analyzing the Complexity of Behavioural Factors Influencing Weight in Adults , 2018 .

[54]  Donglan Zhang,et al.  An Agent-Based Model of Healthy Eating with Applications to Hypertension , 2018 .

[55]  Gabriel A. Wainer,et al.  ANALYZING AND SIMPLIFYING MODEL UNCERTAINTY IN FUZZY COGNITIVE MAPS , 2017 .

[56]  Abdulrahman M El-Sayed,et al.  Stigma and the etiology of depression among the obese: An agent-based exploration. , 2016, Social science & medicine.

[57]  Bruce Edmonds,et al.  The Aqua Book: Guidance on Producing Quality Analysis for Government by HM Treasury , 2016, J. Artif. Soc. Soc. Simul..

[58]  S. Page,et al.  Leveraging social influence to address overweight and obesity using agent-based models: the role of adolescent social networks. , 2015, Social science & medicine.

[59]  Philippe J. Giabbanelli,et al.  Modelling the Joint Effect of Social Determinants and Peers on Obesity Among Canadian Adults , 2014, Theories and Simulations of Complex Social Systems.

[60]  Nadia Hashem,et al.  "I" and "others" , 2013 .

[61]  Vahid Dabbaghian,et al.  Modeling the influence of social networks and environment on energy balance and obesity , 2012, J. Comput. Sci..

[62]  Michael R Flynn,et al.  Fitting human exposure data with the Johnson SB distribution , 2006, Journal of Exposure Science and Environmental Epidemiology.

[63]  K. Ball,et al.  The role of socio-cultural factors in the obesity epidemic , 2005 .

[64]  Milton C Weinstein,et al.  Principles of good practice for decision analytic modeling in health-care evaluation: report of the ISPOR Task Force on Good Research Practices--Modeling Studies. , 2003, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[65]  J. E. Harkaway Obesity and systems research: The complexity of studying complexities. , 2000 .

[66]  Roberto Leombruni,et al.  A Common Protocol for Agent-Based Social Simulation , 2006, J. Artif. Soc. Soc. Simul..

[67]  J. Kleijnen Verification and Validation of Simulation Models , 2022 .