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"Anarchy" Reigns: A Quantitative Analysis of Agent-Based Modelling Publication Practices in JASSS, 2001-2012
By: Simon Angus, Behrooz Hassani-Mahmooei, Volume 18 (4)
Abstract: Agent Based Modelling (ABM), a promising scientific toolset, has received criticism from some, in part, due to a claimed lack of scientific rigour, especially in the communication of its methods and results. To test the veracity of these claims, we conduct a structured analysis of over 900 scientific objects (figures, tables, or equations) that arose from 128 ABM papers published in the Journal of Artificial Societies and Social Simulation (JASSS), during the period 2001 to 2012 inclusive. Regrettably, we find considerable evidence in support of the detractors of ABM as a scientific enterprise ...

Agent-Based Modelling of Social-Ecological Systems: Achievements, Challenges, and a Way Forward
By: Jule Thober, Birgit Müller, Jürgen Groeneveld, Volker Grimm, Volume 20 (2)
Abstract: Understanding social-ecological systems (SES) is crucial to supporting the sustainable management of resources. Agent-based modelling is a valuable tool to achieve this because it can represent the behaviour and interactions of organisms, human actors and institutions. Agent-based models (ABMs) have therefore already been widely used to study SES. However, ABMs of SES are by their very nature complex. They are therefore difficult to parameterize and analyse, which can limit their usefulness. It is time to critically reflect upon the current state-of-the-art to evaluate to what degree the poten ...

An Empirically Grounded Model of Green Electricity Adoption in Germany: Calibration, Validation and Insights into Patterns of Diffusion
By: Friedrich Krebs, Volume 20 (2)
Abstract: Spatially explicit agent-based models (ABM) of innovation diffusion have experienced growing attention over the last few years. The ABM presented in this paper investigates the adoption of green electricity tariffs by German households. The model represents empirically characterised household types as agent types which differ in their decision preferences regarding green electricity and other psychological properties. Agent populations are initialised based on spatially explicit socio demographic data describing the sociological lifestyles found in Germany. For model calibration and validation ...

Modeling Organizational Cognition: The Case of Impact Factor
By: Davide Secchi, Stephen J. Cowley, Volume 21 (1)
Abstract: This article offers an alternative perspective on organizational cognition based on e-cognition whereby appeal to systemic cognition replaces the traditional computational model of the mind that is still extremely popular in organizational research. It uses information processing, not to explore inner processes, but as the basis for pursuing organizational matters. To develop a theory of organizational cognition, the current work presents an agent-based simulation model based on the case of how individual perception of scientific value is affected by and affects organizational intelligence u ...

Automated Analysis of Regularities Between Model Parameters and Output Using Support Vector Regression in Conjunction with Decision Trees
By: Mert Edali, Gönenç Yücel, Volume 21 (4)
Abstract: Opening the black-box of nonlinear relationships between model inputs and outputs, significantly contributes to the understanding of the dynamic problem being studied. Considering the weaknesses and disadvantages of human-guided and systematic techniques offered in the literature, this paper presents a model analysis and exploration tool for agent-based models. The tool first approximates input-output relationships by developing a metamodel, a simplified representation of the original agent-based model. For this purpose, it utilizes support vector regression, which is capable of approximating ...

An Agent-Based Model of Rural Households’ Adaptation to Climate Change
By: Atesmachew Hailegiorgis, Andrew Crooks, Claudio Cioffi-Revilla, Volume 21 (4)
Abstract: Future climate change is expected to have greater impacts on societies whose livelihoods rely on subsistence agricultural systems. Adaptation is essential for mitigating adverse effects of climate change, to sustain rural livelihoods and ensure future food security. We present an agent-based model, called OMOLAND-CA, which explores the impact of climate change on the adaptive capacity of rural communities in the South Omo Zone of Ethiopia. The purpose of the model is to answer research questions on the resilience and adaptive capacity of rural households with respect to variations in climate, ...

Calibrating Agent-Based Models with Linear Regressions
By: Ernesto Carrella, Richard Bailey, Jens Koed Madsen, Volume 23 (1)
Abstract: In this paper, we introduce a simple way to parametrize simulation models by using regularized linear regression. Regressions bypass the three major challenges of calibrating by minimization: selecting the summary statistics, defining the distance function and minimizing it numerically. By substituting regression with classification, we can extend this approach to model selection. We present five example estimations: a statistical fit, a biological individual-based model, a simple real business cycle model, a non-linear biological simulation and heuristics selection in a fishery agent-based mo ...

‘One Size Does Not Fit All’: A Roadmap of Purpose-Driven Mixed-Method Pathways for Sensitivity Analysis of Agent-Based Models
By: Arika Ligmann-Zielinska, Peer-Olaf Siebers, Nicholas Magliocca, Dawn C. Parker, Volker Grimm, Jing Du, Martin Cenek, Viktoriia Radchuk, Nazia N. Arbab, Sheng Li, Uta Berger, Rajiv Paudel, Derek T. Robinson, Piotr Jankowski, Li An, Xinyue Ye, Volume 23 (1)
Abstract: Designing, implementing, and applying agent-based models (ABMs) requires a structured approach, part of which is a comprehensive analysis of the output to input variability in the form of uncertainty and sensitivity analysis (SA). The objective of this paper is to assist in choosing, for a given ABM, the most appropriate methods of SA. We argue that no single SA method fits all ABMs and that different methods of SA should be used based on the overarching purpose of the model. For example, abstract exploratory models that focus on a deeper understanding of the target system and its properties a ...

No Free Lunch when Estimating Simulation Parameters
By: Ernesto Carrella, Volume 24 (2)
Abstract: In this paper, we have estimated the parameters of 41 simulation models to find which of 9 estimation algorithms performs better. Unfortunately, no single algorithm was the best for all or even most of the models. Rather, five main results emerge from this research. First, each algorithm was the best estimator for at least one parameter. Second, the best estimation algorithm varied not only between models but even between parameters of the same model. Third, each estimation algorithm failed to estimate at least one identifiable parameter. Fourth, choosing the right algorithm improved estimatio ...

Multimodal Evolutionary Algorithms for Easing the Complexity of Agent-Based Model Calibration
By: Juan Francisco Robles, Enrique Bermejo, Manuel Chica, Óscar Cordón, Volume ()
Abstract: Agent-based modelling usually involves a calibration stage where a set of parameters needs to be estimated. The calibration process can be automatically performed by using calibration algorithms which search for an optimal parameter configuration to obtain quality model fittings. This issue makes the use of multimodal optimisation methods interesting for calibration as they can provide diverse solution sets with similar and optimal fitness. In this contribution, we compare nine competitive multimodal evolutionary algorithms, both classical and recent, to calibrate agent-based models. We analys ...