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68 articles matched your search for the keywords:
Agent-Based Modelling, Differential School Effectiveness, Multilevel Modelling, Peer Effects, Teacher Expectation Bias

The Multi-Agent Modelling Language and the Model Design Interface

László Gulyás, Tamás Kozsik and John B. Corliss
Journal of Artificial Societies and Social Simulation 2 (3) 8

Kyeywords: Social Science Simulation, Agent-Based Modelling, Integrated Modelling Environment
Abstract: While computer models provide many advantages over traditional experimental methods, they also raise several problems. The process of software development is a complicated task with high potential for errors, especially when it is carried out by scientists holding their expertise in other fields than computer science. On the other hand, the process of creating computer simulations of social systems which reflect the reality of such systems requires insights considerably beyond expertise in computer science. The Multi-Agent Modelling Language (MAML) is one of the efforts to ease these difficulties. In its current version, MAML is a macro-language for Swarm (a freely distributed toolset under development at SFI), but it is also part of a larger Swarm-independent framework. Also, the design of MAML, while influenced by concepts from Swarm, is general enough to allow for later extension of the supported simulation kernels. This paper gives an overview of the mentioned larger framework, with special emphasis on MAML and its graphical CASE tool, the Model Design Interface.

Intervening to Achieve Co-Operative Ecosystem Management: Towards an Agent Based Model

Jim Doran
Journal of Artificial Societies and Social Simulation 4 (2) 4

Kyeywords: Software Agent, Agent-Based Modelling, Integrated Watershed Management, Sustainability, Fraser River, Intervention Strategy
Abstract: We propose an advanced agent-based modelling approach to ecosystem management, informed and motivated by consideration of the Fraser River watershed and its management problems. Agent-based modelling is introduced, and a three-stage computer-based research programme is formulated, the focus of which is on how best to intervene to cause stakeholders to co-operate effectively in ecosystem management, and on the objective discovery and comparison of intervention strategies by way of computer experimentation. The agent-based model outlined is technically relatively complex, and several potential difficulties in its detailed development are discussed. Types of ecosystem intervention strategy that might plausibly be discovered or recommended by the model are projected and compared with those currently advocated in the literature.

Lake Anderson Revisited by Agents

Michael Moehring and Klaus G. Troitzsch
Journal of Artificial Societies and Social Simulation 4 (3) 1

Kyeywords: Water Management, Stepwise Refinement, Multilevel Modelling
Abstract: In our paper, we replicate simulation experiments carried out some 30 years ago by Jay M. Anderson who then tried to find out which measures should be taken to avoid the eutrophication of a lake. In his DYNAMO model, he simulated the development of a lake under cultural eutrophication, i.e. mainly by the discharge of fertilisers from agriculture. He designed a number of policies and applied them as an experimenter. In our model, some of the policies suggested by Anderson are taken by a government (or, alternatively, by a number of regional governments) who are in charge of the region(s) around the lake. We define rules which the authorities apply when they find that some of the variables which describe the state of the lake exceed (or fall below) certain thresholds. In a next step of refinement of the model, authorities will still define thresholds, but will not take all possible measures themselves, but charge the farmers with taxes when they exceed the fertiliser discharge limit. Farmers will then be endowed with rules which tell them whether it is better for them to pay the taxes or take appropriate measures against eutrophication themselves. The rationale of our paper is to show how stepwise refinement of a model can contribute to our understanding of the interactions between water resource decision makers of different levels and the natural environment. It is part of our efforts to develop agent-based models for application to issues of water treatment - as is done in the FIRMA project

An Agent-Based Model of Ethnic Mobilisation

Armano Srbljinovic, Drazen Penzar, Petra Rodik and Kruno Kardov
Journal of Artificial Societies and Social Simulation 6 (1) 1

Kyeywords: Agent-Based Modelling; Ethnic Identity; Ethnic Mobilisation
Abstract: In this paper we used the methodology of agent-based modelling to help explaining why populations with very similar socio-demographic characteristics sometimes exhibit great differences in ethnic mobilisation levels during mobilisation processes. This agent-based model of ethnic mobilisation was inspired and developed by combining and extending several theories, ideas and modelling constructs that were already used in agent-based modelling of social processes. The model has been specifically adapted to account for some of the most important characteristics of ethnic mobilisation processes that took place in the former Yugoslavia. Results obtained by experimenting with the model indicate that the observed differences in mobilisation levels across populations may sometimes not be related to the variations within any particular socio-demographic factor, but merely to random differences in the initial states of the individuals. In this model these random differences primarily relate to the degrees of importance that individuals attach to their ethnic identity, as well as to the layout of social networks.

A Model for a Simple Luhmann Economy

Anselm Fleischmann
Journal of Artificial Societies and Social Simulation 8 (2) 4

Kyeywords: Agent-Based Modelling, Luhmann Economy, Fuzzy Clustering
Abstract: The core of this work is the definition of an agent-based model for a simple Luhmann economy based on publications of Niklas Luhmann. • Using an implementation on a default personal computer the behaviour of the model is studied when assumptions regarding initial conditions are made. Fuzzy-c-means clustering is used as visualisation aid. The impact of the observation horizon (a model parameter determining how far agents can see) is studied interactively. • Solution paths of the Luhmann economy originating from an initial endowment to equilibrium (when the economy settles down) are studied. • The impact of model parameters determining the unevenness regarding the initial distribution of wealth is studied by Monte Carlo simulation. Niklas Luhmann\'s hypothesis, that the economy starts from and produces further inequality in order to continue (see Luhmann 1988, p. 112) could be reproduced by computer simulation. The main characteristic of the approach is the consideration of the cohesive structure of communication (i.e. one communicative act - many understanding observers) also prominent in (Dunbar 1996, pp. 192-207). The model gives directions how to model further aspects of Niklas Luhmann\'s theory.

Appearances Can Be Deceiving: Lessons Learned Re-Implementing Axelrod's 'Evolutionary Approach to Norms'

José Manuel Galán and Luis R. Izquierdo
Journal of Artificial Societies and Social Simulation 8 (3) 2

Kyeywords: Replication, Agent-Based Modelling, Evolutionary Game Theory, Social Dilemmas, Norms, Metanorms
Abstract: In this paper we try to replicate the simulation results reported by Axelrod (1986) in an influential paper on the evolution of social norms. Our study shows that Axelrod's results are not as reliable as one would desire. We can obtain the opposite results by running the model for longer, by slightly modifying some of the parameters, or by changing some arbitrary assumptions in the model. This re-implementation exercise illustrates the importance of running stochastic simulations several times for many periods, exploring the parameter space adequately, complementing simulation with analytical work, and being aware of the scope of our simulation models.

Uncertainty and Cooperation: Analytical Results and a Simulated Agent Society

Peter Andras, John Lazarus, Gilbert Roberts and Steven J Lynden
Journal of Artificial Societies and Social Simulation 9 (1) 7

Kyeywords: Agent-Based Modelling, Cooperation, Social Interaction Simulation, Uncertainty
Abstract: Uncertainty is an important factor that influences social evolution in natural and artificial environments. Here we distinguish between three aspects of uncertainty. Environmental uncertainty is the variance of resources in the environment, perceived uncertainty is the variance of the resource distribution as perceived by the organism and effective uncertainty is the variance of resources effectively enjoyed by individuals. We show analytically that perceived uncertainty is larger than environmental uncertainty and that effective uncertainty is smaller than perceived uncertainty, when cooperation is present. We use an agent society simulation in a two dimensional world for the generation of simulation data as one realisation of the analytical results. Together with our earlier theoretical work, results here show that cooperation can buffer the detrimental effects of uncertainty on the organism. The proposed conceptualisation of uncertainty can help in understanding its effects on social evolution and in designing artificial social environments.

Self-Organizing Traffic at a Malfunctioning Intersection

Sujai Kumar and Sugata Mitra
Journal of Artificial Societies and Social Simulation 9 (4) 3

Kyeywords: Self-Organizing Systems, Complex Systems, Traffic, Emergent Behaviour, Agent-Based Modelling, Rule-Breaking
Abstract: Traffic signals and traffic flow models have been studied extensively in the past and have provided valuable insights on the design of signalling systems, congestion control, and punitive policies. This paper takes a slightly different tack and describes what happens at an intersection where the traffic signals are malfunctioning and stuck in some configuration. By modelling individual vehicles as agents, we were able to replicate the surprisingly organized traffic flow that we observed at a real malfunctioning intersection in urban India. Counter-intuitively, the very lawlessness that normally causes jams was causing traffic to flow smoothly at this intersection. We situate this research in the context of other research on emergent complex phenomena in traffic, and suggest further lines of research that could benefit from the analysis and modelling of rule-breaking behaviour.

An Agent-Based Representation of the Garbage Can Model of Organizational Choice

Guido Fioretti and Alessandro Lomi
Journal of Artificial Societies and Social Simulation 11 (1) 1

Kyeywords: Organization Theory, Garbage Can Model, Agent-Based Modelling
Abstract: Cohen, March and Olsen\'s Garbage Can Model (GCM) of organizational choice represent perhaps the first – and remains by far the most influential –agent-based representation of organizational decision processes. According to the GCM organizations are conceptualized as crossroads of time-dependent flows of four distinct classes of objects: \'participants,\' \'opportunities,\' \'solutions\' and \'problems.\' Collisions among the different objects generate events called \'decisions.\' In this paper we use NetLogo to build an explicit agent-based representation of the original GCM. We conduct a series of simulation experiments to validate and extend some of the most interesting conclusions of the GCM. We show that our representation is able to reproduce a number of properties of the original model. Yet, unlike the original model, in our representation these properties are not encoded explicitly, but emerge from general principles of the Garbage Can decision processes.

Progress in Model-To-Model Analysis

Juliette Rouchier, Claudio Cioffi-Revilla, J. Gareth Polhill and Keiki Takadama
Journal of Artificial Societies and Social Simulation 11 (2) 8

Kyeywords: Social Simulation, Agent-Based Modelling, Comparative Computational Methodology, Validation, Replication
Abstract: [No abstract]

A Replication That Failed - on the Computational Model in 'Michael W. Macy and Yoshimichi Sato: Trust, Cooperation and Market Formation in the U.S. and Japan. Proceedings of the National Academy of Sciences, May 2002'

Oliver Will and Rainer Hegselmann
Journal of Artificial Societies and Social Simulation 11 (3) 3

Kyeywords: Replication, Social Dilemmas, Simulation Methodology, Cooperation, Trust, Agent-Based Modelling
Abstract: The article describes how and why we failed to replicate main effects of a computational model that Michael Macy and Yoshimichi Sato published in the Proceedings of the National Academy of Sciences (May 2002). The model is meant to answer a fundamental question about social life: Why, when and how is it possible to build trust with distant people? Based on their model, Macy and Sato warn the US society about an imminent danger: the possible break down of trust caused by too much social mobility. But the computational evidence for exactly that result turned out not to be replicable.

Modelling Socio-Technical Transition Patterns and Pathways

Noam Bergman, Alex Haxeltine, Lorraine Whitmarsh, Jonathan Köhler, Michel Schilperoord and Jan Rotmans
Journal of Artificial Societies and Social Simulation 11 (3) 7

Kyeywords: Complex Systems, Agent-Based Modelling, Social Simulation, Transitions, Transition Theory
Abstract: We report on research that is developing a simulation model for assessing systemic innovations, or 'transitions', of societal systems towards a more sustainable development. Our overall aim is to outline design principles for models that can offer new insights into tackling persistent problems in large-scale systems, such as the European road transport system or the regional management of water resources. The systemic nature of these problems is associated with them being complex, uncertain and cutting across a number of sectors, and indicates a need for radical technological and behavioural solutions that address changes at the systems level rather than offering incremental changes within sub-systems. Model design is inspired by recent research into transitions, an emerging paradigm which provides a framework for tackling persistent problems. We use concepts from the literature on transitions to develop a prototype of a generic 'transition model'. Our prototype aims to capture different types of transition pathways, using historical examples such as the transition from horse-drawn carriages to cars or that from sailing ships to steam ships. The model combines agent-based modelling techniques and system dynamics, and includes interactions of individual agents and sub-systems, as well as cumulative effects on system structures. We show success in simulating different historical transition pathways by adapting the model's parameters and rules for each example. Finally, we discuss the improvements necessary for systematically exploring and detailing transition pathways in empirical case-study applications to current and future transitions such as the transition to a sustainable transport system in Europe.

Reply to Will and Hegselmann

Michael Macy and Yoshimichi Sato
Journal of Artificial Societies and Social Simulation 11 (4) 11

Kyeywords: Replication, Social Dilemmas, Simulation Methodology, Cooperation, Trust, Agent-Based Modelling
Abstract: [No abstract]

Errors and Artefacts in Agent-Based Modelling

José Manuel Galán, Luis R. Izquierdo, Segismundo S. Izquierdo, José Ignacio Santos, Ricardo del Olmo, Adolfo López-Paredes and Bruce Edmonds
Journal of Artificial Societies and Social Simulation 12 (1) 1

Kyeywords: Verification, Replication, Artefact, Error, Agent-Based Modelling, Modelling Roles
Abstract: The objectives of this paper are to define and classify different types of errors and artefacts that can appear in the process of developing an agent-based model, and to propose activities aimed at avoiding them during the model construction and testing phases. To do this in a structured way, we review the main concepts of the process of developing such a model – establishing a general framework that summarises the process of designing, implementing, and using agent-based models. Within this framework we identify the various stages where different types of errors and artefacts may appear. Finally we propose activities that could be used to detect (and hence eliminate) each type of error or artefact.

Games on Cellular Spaces: How Mobility Affects Equilibrium

Pedro Ribeiro de Andrade, Antonio Miguel Vieira Monteiro, Gilberto Câmara and Sandra Sandri
Journal of Artificial Societies and Social Simulation 12 (1) 5

Kyeywords: Spatial Games, Agent-Based Modelling, Mobility, Satisfaction, Chicken Game, Nash Equilibrium
Abstract: In this work we propose a new model for spatial games. We present a definition of mobility in terms of the satisfaction an agent has with its spatial location. Agents compete for space through a non-cooperative game by using mixed strategies. We are particularly interested in studyig the relation between Nash equilibrium and the winner strategy of a given model with mobility, and how the mobility can affect the results. The experiments show that mobility is an important variable concerning spatial games. When we change parameters that affect mobility, it may lead to the success of strategies away from Nash equilibrium.

Agent Street: An Environment for Exploring Agent-Based Models in Second Life

Andrew Crooks, Andrew Hudson-Smith and Joel Dearden
Journal of Artificial Societies and Social Simulation 12 (4) 10

Kyeywords: Agent-Based Modelling, Pedestrian Evacuation, Segregation, Virtual Worlds, Second Life
Abstract: Urban models can be seen on a continuum between iconic and symbolic. Generally speaking, iconic models are physical versions of the real world at some scaled down representation, while symbolic models represent the system in terms of the way they function replacing the physical or material system by some logical and/or mathematical formulae. Traditionally iconic and symbolic models were distinct classes of model but due to the rise of digital computing the distinction between the two is becoming blurred, with symbolic models being embedded into iconic models. However, such models tend to be single user. This paper demonstrates how 3D symbolic models in the form of agent-based simulations can be embedded into iconic models using the multi-user virtual world of Second Life. Furthermore, the paper demonstrates Second Life\'s potential for social science simulation. To demonstrate this, we first introduce Second Life and provide two exemplar models; Conway\'s Game of Life, and Schelling\'s Segregation Model which highlight how symbolic models can be viewed in an iconic environment. We then present a simple pedestrian evacuation model which merges the iconic and symbolic together and extends the model to directly incorporate avatars and agents in the same environment illustrating how \'real\' participants can influence simulation outcomes. Such examples demonstrate the potential for creating highly visual, immersive, interactive agent-based models for social scientists in multi-user real time virtual worlds. The paper concludes with some final comments on problems with representing models in current virtual worlds and future avenues of research.

A Pragmatic Reading of Friedman's Methodological Essay and What It Tells Us for the Discussion of ABMs

Simon Deichsel and Andreas Pyka
Journal of Artificial Societies and Social Simulation 12 (4) 6

Kyeywords: Methodology, Agent-Based Modelling, Assumptions, Calibration
Abstract: The issues of empirical calibration of parameter values and functional relationships describing the interactions between the various actors plays an important role in agent based modelling. Agent-based models range from purely theoretical exercises focussing on the patterns in the dynamics of interactions processes to modelling frameworks which are oriented closely at the replication of empirical cases. ABMs are classified in terms of their generality and their use of empirical data. In the literature the recommendation can be found to aim at maximizing both criteria by building so-called 'abductive models'. This is almost the direct opposite of Milton Friedman's famous and provocative methodological credo 'the more significant a theory, the more unrealistic the assumptions'. Most methodologists and philosophers of science have harshly criticised Friedman's essay as inconsistent, wrong and misleading. By presenting arguments for a pragmatic reinterpretation of Friedman's essay, we will show why most of the philosophical critique misses the point. We claim that good simulations have to rely on assumptions, which are adequate for the purpose in hand and those are not necessarily the descriptively accurate ones.

Sendero: An Extended, Agent-Based Implementation of Kauffman's NKCS Model

Julian Padget, Richard Vidgen, James Mitchell, Amy Marshall and Rick Mellor
Journal of Artificial Societies and Social Simulation 12 (4) 8

Kyeywords: Coevolution, Agent-Based Modelling, NK, NKCS, Fitness Landscape
Abstract: The idea of agents exploring a fitness landscape in which they seek to move from 'fitness valleys' to higher 'fitness peaks' has been presented by Kauffman in the NK and NKCS models. The NK model addresses single species while the NKCS extension illustrates coevolving species on coupled fitness landscapes. We describe an agent-based simulation (Sendero), built in Repast, of the NK and NKCS models. The results from Sendero are validated against Kauffman's findings for the NK and NKCS models. We also describe extensions to the basic model, including population dynamics and communication networks for NK, and directed graphs and variable change rates for NKCS. The Sendero software is available as open source under the BSD licence and is thus available for download and extension by the research community.

What Do Agent-Based and Equation-Based Modelling Tell Us About Social Conventions: The Clash Between ABM and EBM in a Congestion Game Framework

Federico Cecconi, Marco Campenni, Giulia Andrighetto and Rosaria Conte
Journal of Artificial Societies and Social Simulation 13 (1) 6

Kyeywords: Agent-Based Modelling, Equation-Based Modelling, Congestion Game, Model of Social Phenomena
Abstract: In this work simulation-based and analytical results on the emergence steady states in traffic-like interactions are presented and discussed. The objective of the paper is twofold: i) investigating the role of social conventions in coordination problem situations, and more specifically in congestion games; ii) comparing simulation-based and analytical results to figure out what these methodologies can tell us on the subject matter. Our main issue is that Agent-Based Modelling (ABM) and the Equation-Based Modelling (EBM) are not alternative, but in some circumstances complementary, and suggest some features distinguishing these two ways of modeling that go beyond the practical considerations provided by Parunak H.V.D., Robert Savit and Rick L. Riolo. Our model is based on the interaction of strategies of heterogeneous agents who have to cross a junction. In each junction there are only four inputs, each of which is passable only in the direction of the intersection and can be occupied only by an agent one at a time. The results generated by ABM simulations provide structured data for developing the analytical model through which generalizing the simulation results and make predictions. ABM simulations are artifacts that generate empirical data on the basis of the variables, properties, local rules and critical factors the modeler decides to implement into the model; in this way simulations allow generating controlled data, useful to test the theory and reduce the complexity, while EBM allows to close them, making thus possible to falsify them.

Using Qualitative Evidence to Enhance an Agent-Based Modelling System for Studying Land Use Change

J. Gareth Polhill, Lee-Ann Sutherland and Nicholas M. Gotts
Journal of Artificial Societies and Social Simulation 13 (2) 10

Kyeywords: Agent-Based Modelling, Land Use/Cover Change, Qualitative Research, Interdisciplinary Research
Abstract: 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.

Social Simulation and Analysis of the Dynamics of Criminal Hot Spots

Tibor Bosse and Charlotte Gerritsen
Journal of Artificial Societies and Social Simulation 13 (2) 5

Kyeywords: Agent-Based Modelling, Criminal Hot Spots, Displacement, Reputation, Social Simulation, Analysis
Abstract: Within the field of Criminology, the spatio-temporal dynamics of crime are an important subject of study. In this area, typical questions are how the behaviour of offenders, targets, and guardians can be explained and predicted, as well as the emergence and displacement of criminal hot spots. In this article we present a combination of software tools that can be used as an experimental environment to address such questions. In particular, these tools comprise an agent-based simulation model, a verification tool, and a visualisation tool. The agent-based simulation model specifically focuses on the interplay between hot spots and reputation. Using this environment, a large number of simulation runs have been performed, of which results have been formally analysed. Based on these results, we argue that the presented environment offers a valuable approach to analyse the dynamics of criminal hot spots.

Agent-Based Modelling: The Next 15 Years

Lynne Hamill
Journal of Artificial Societies and Social Simulation 13 (4) 7

Kyeywords: Agent-Based Modelling,, NetLogo, Policy Advice
Abstract: This short note makes recommendations for the future direction of research in agent-based modelling (ABM). It is a personal view based on my experience as a policy adviser who has recently come to ABM. I suggest that to promote the use of ABM, the ABM community needs demonstrate the value of modelling to other social scientists by showing-by-doing and offering training projects; and to produce tools, guidance on good-practice and basic building blocks. Then the policy contexts most likely to benefit from ABM need to be identified along with any new data requirements, so that the usefulness of ABM can be demonstrated to policy analysts. This is, in my view, the challenge facing the ABM community for the next 15 years.

Diffusion of Competing Innovations: The Effects of Network Structure on the Provision of Healthcare

Adam G. Dunn and Blanca Gallego
Journal of Artificial Societies and Social Simulation 13 (4) 8

Kyeywords: Innovation Diffusion, Scale-Free Networks, Health Policy, Agent-Based Modelling
Abstract: Medical innovations, in the form of new medication or other clinical practices, evolve and spread through health care systems, impacting on the quality and standards of health care provision, which is demonstrably heterogeneous by geography. Our aim is to investigate the potential for the diffusion of innovation to influence health inequality and overall levels of recommended care. We extend existing diffusion of innovation models to produce agent-based simulations that mimic population-wide adoption of new practices by doctors within a network of influence. Using a computational model of network construction in lieu of empirical data about a network, we simulate the diffusion of competing innovations as they enter and proliferate through a state system comprising 24 geo-political regions, 216 facilities and over 77,000 individuals. Results show that stronger clustering within hospitals or geo-political regions is associated with slower adoption amongst smaller and rural facilities. Results of repeated simulation show how the nature of uptake and competition can contribute to low average levels of recommended care within a system that relies on diffusive adoption. We conclude that an increased disparity in adoption rates is associated with high levels of clustering in the network, and the social phenomena of competitive diffusion of innovation potentially contributes to low levels of recommended care.

A First Approach on Modelling Staff Proactiveness in Retail Simulation Models

Peer-Olaf Siebers and Uwe Aickelin
Journal of Artificial Societies and Social Simulation 14 (2) 2

Kyeywords: Retail Performance, Management Practices, Proactive Behaviour, Service Experience, Agent-Based Modelling, Simulation
Abstract: There has been a noticeable shift in the relative composition of the industry in the developed countries in recent years; manufacturing is decreasing while the service sector is becoming more important. However, currently most simulation models for investigating service systems are still built in the same way as manufacturing simulation models, using a process-oriented world view, i.e. they model the flow of passive entities through a system. These kinds of models allow studying aspects of operational management but are not well suited for studying the dynamics that appear in service systems due to human behaviour. For these kinds of studies we require tools that allow modelling the system and entities using an object-oriented world view, where intelligent objects serve as abstract \'actors\' that are goal directed and can behave proactively. In our work we combine process-oriented discrete event simulation modelling and object-oriented agent based simulation modelling to investigate the impact of people management practices on retail productivity. In this paper, we reveal in a series of experiments what impact considering proactivity can have on the output accuracy of simulation models of human centric systems. The model and data we use for this investigation are based on a case study in a UK department store. We show that considering proactivity positively influences the validity of these kinds of models and therefore allows analysts to make better recommendations regarding strategies to apply people management practices.

Modelling Theory Communities in Science

Petra Ahrweiler
Journal of Artificial Societies and Social Simulation 14 (4) 8

Kyeywords: Simulating Science, Theory Interaction, Agent-Based Modelling, Theory Network
Abstract: This position paper presents a framework for modelling theory communities where theories interact as agents in a conceptual network. It starts with introducing the difficulties in integrating scientific theories by discussing some recent approaches, especially of structuralist theory of science. Theories might differ in reference, extension, scope, objectives, functions, architecture, language etc. To address these potential integration barriers, the paper employs a broad definition of "scientific theory", where a theory is a more or less complex description a describer puts forward in a context called science with the aim of making sense of the world. This definition opens up the agency dimension of theories: theories "do" something. They work on a - however ontologically interpreted - subject matter. They describe something, and most of them claim that their descriptions of this "something" are superior to those of others. For modelling purposes, the paper makes use of such description behaviour of scientific theories on two levels. The first is the level where theories describe the world in their terms. The second is a sub-case of the first: theories can of course describe the description behaviour of other theories concerning this world and compare with own description behaviour. From here, interaction and potential cooperation between theories could be potentially identified by each theory perspective individually. Generating inclusive theory communities and simulating their dynamics using an agent-based model means to implement theories as agents; to create an environment where the agents work as autonomous entities in a self-constituted universe of discourse; to observe what they do with this environment (they will try to apply their concepts, and instantiate their mechanisms of sense-making); and to let them mutually describe and analyse their behaviour and suggest areas for interaction. Some mechanisms for compatibility testing are discussed and the prototype of the model with preliminary applications is introduced.

ABMland - a Tool for Agent-Based Model Development on Urban Land Use Change

Nina Schwarz, Daniel Kahlenberg, Dagmar Haase and Ralf Seppelt
Journal of Artificial Societies and Social Simulation 15 (2) 8

Kyeywords: Agent-Based Modelling, Urban, Land Use, Repast
Abstract: Modelling urban land use change can foster understanding of underlying processes and is increasingly realized using agent-based models (ABM) as they allow for explicitly coding land management decisions. However, urban land use change is the result of interactions of a variety of individuals as well as organisations. Thus, simulation models on urban land use need to include a diversity of agent types which in turn leads to complex interactions and coding processes. This paper presents the new ABMland tool which can help in this process: It is software for developing agent-based models for urban land use change within a spatially explicit and joint environment. ABMland allows for implementing agent-based models and parallel model development while simplifying the coding process. Six major agent types are already included as coupled models: residents, planners, infrastructure providers, businesses, developers and lobbyists. Their interactions are pre-defined and ensure valid communication during the simulation. The software is implemented in Java building upon Repast Simphony and other libraries.

Agent-Based Modelling: Tools for Linking NetLogo and r

Jan C. Thiele, Winfried Kurth and Volker Grimm
Journal of Artificial Societies and Social Simulation 15 (3) 8

Kyeywords: Agent-Based Modelling, Design of Experiments, R, NetLogo, Model Analysis, Modelling Software
Abstract: A seamless integration of software platforms for implementing agent-based models and for analysing their output would facilitate comprehensive model analyses and thereby make agent-based modelling more useful. Here we report on recently developed tools for linking two widely used software platforms: NetLogo for implementing agent-based models, and R for the statistical analysis and design of experiments. Embedding R into NetLogo allows the use of advanced statistical analyses, specific statistical distributions, and advanced tools for visualization from within NetLogo programs. Embedding NetLogo into R makes it possible to design simulation experiments and all settings for analysing model output from the outset, using R, and then embed NetLogo programs in this virtual laboratory. Our linking tools have the potential to significantly advance research based on agent-based modelling.

Asking the Oracle: Introducing Forecasting Principles into Agent-Based Modelling

Samer Hassan, Javier Arroyo, José Manuel Galán, Luis Antunes and Juan Pavón
Journal of Artificial Societies and Social Simulation 16 (3) 13

Kyeywords: Forecasting, Guidelines, Prediction, Agent-Based Modelling, Modelling Process, Social Simulation
Abstract: This paper presents a set of guidelines, imported from the field of forecasting, that can help social simulation and, more specifically, agent-based modelling practitioners to improve the predictive performance and the robustness of their models. The presentation starts with a discussion on the current debate on prediction in social processes, followed by an overview of the recent experience and lessons learnt from the field of forecasting. This is the basis to define standard practices when developing agent-based models under the perspective of forecasting experimentation. In this context, the guidelines are structured in six categories that correspond to key issues that should be taken into account when building a predictor agent-based model: the modelling process, the data adequacy, the space of solutions, the expert involvement, the validation, and the dissemination and replication. The application of these guidelines is illustrated with an existing agent-based model. We conclude by tackling some intrinsic difficulties that agent-based modelling often faces when dealing with prediction models.

Pitfalls in Spatial Modelling of Ethnocentrism: A Simulation Analysis of the Model of Hammond and Axelrod

Fredrik Jansson
Journal of Artificial Societies and Social Simulation 16 (3) 2

Kyeywords: Agent-Based Modelling, Ethnocentrism, Prisoners'' Dilemma, Spatial Interactions, Validation
Abstract: Ethnocentrism refers to the tendency to behave differently towards strangers based only on whether they belong to the ingroup or the outgroup. It is a widespread phenomenon that can be triggered by arbitrary cues, but the origins of which is not clearly understood. In a recent simulation model by Hammond and Axelrod, an ingroup bias evolves in the prisoner's dilemma game. However, it will be argued here that the model does little to advance our understanding of ethnocentrism. The model assumes a spatial structure in which agents interact only with their immediate neighbourhood, populated mostly by clones, and the marker becomes an approximate cue of whether the partner is one. It will be shown that agents with an ingroup bias are successful compared to unconditional co-operators since they only exclude non-clones, but are outcompeted by less error-prone kin identifiers. Thus, the results of the simulations can be explained by a simple form of kin selection. These findings illustrate how spatial assumptions can alter a model to the extent that it no longer describes the phenomenon under study.

Communicating Social Simulation Models to Sceptical Minds

Annie Waldherr and Nanda Wijermans
Journal of Artificial Societies and Social Simulation 16 (4) 13

Kyeywords: Social Simulation, Agent-Based Modelling, Rejective Criticism, Constructive Feedback, Communication, Peer Support
Abstract: When talking to fellow modellers about the feedback we get on our simulation models the conversation quickly shifts to anecdotes of rejective scepticism. Many of us experience that they get only few remarks, and especially only little helpful constructive feedback on their simulation models. In this forum paper, we give an overview and reflections on the most common criticisms experienced by ABM modellers. Our goal is to start a discussion on how to respond to criticism, and particularly rejective scepticism, in a way that makes it help to improve our models and consequently also increase acceptance and impact of our work. We proceed by identifying common criticism on agent-based modelling and social simulation methods and show where it shifts to rejection. In the second part, we reflect on the reasons for rejecting the agent-based approach, which we mainly locate in a lack of understanding on the one hand, and academic territorialism on the other hand. Finally, we also give our personal advice to socsim modellers of how to deal with both forms of rejective criticism.

About the Uncertainties in Model Design and Their Effects: An Illustration with a Land-Use Model

Julia Schindler
Journal of Artificial Societies and Social Simulation 16 (4) 6

Kyeywords: Agent-Based Modelling, Policy-Support-Tool, Critique, Justification, Land Use
Abstract: Although agent-based modeling is a strong modelling method in many aspects, its high degree of freedom in agent design can also be regarded as weakness. This freedom requires strong validation strategies during model design for empirical models, especially when models aim to be descriptive enough for policy support. Where theory or evidence does not support model design, assumptions are usually made. In these cases, arguments should be given for why the assumptions do not impair the validity of results. However, we believe that such justifications are sometimes weak in such kinds of models. In particular, we believe that the justification arguments are mostly plausible, but often not strong enough to overrule other plausible arguments leading to different designs. We believe that the reasons for this argumentative ambiguity are sometimes rooted in the type of underlying theory, framework, or validation strategy chosen. The point is that we suspect that simulation results can be sensitive to this ambiguity. To test this hypothesis, we selected a well-tried theory/framework/validation design strategy, and built alternative versions of a land-use change model in line with the underlying strategy. Results clearly show that levels and direction of simulated land-use change are significantly different among model versions.

Modelling Maritime Piracy: A Spatial Approach

Elio Marchione, Shane D Johnson and Alan Wilson
Journal of Artificial Societies and Social Simulation 17 (2) 9

Kyeywords: Maritime Piracy, Crime, Map Generation, Simulation, Agent-Based Modelling
Abstract: This paper presents a model to generate dynamic patterns of maritime piracy. Model details, outputs and calibration are illustrated. The model presented here is a tool to estimate the number of pirates and their area of action. The Gulf of Aden is considered as a case study, and data on pirate attacks, vessels routes and flows through the Gulf of Aden in the year 2010 are used to build the model. Agent-based modelling is employed to simulate pirate, vessel and naval forces behaviours.

Analysing Differential School Effectiveness Through Multilevel and Agent-Based Modelling

Mauricio Salgado, Elio Marchione and Nigel Gilbert
Journal of Artificial Societies and Social Simulation 17 (4) 3

Kyeywords: Agent-Based Modelling, Differential School Effectiveness, Multilevel Modelling, Peer Effects, Teacher Expectation Bias
Abstract: During the last thirty years education researchers have developed models for judging the comparative performance of schools, in studies of what has become known as “differential school effectiveness”. A great deal of empirical research has been carried out to understand why differences between schools might emerge, with variable-based models being the preferred research tool. The use of more explanatory models such as agent-based models (ABM) has been limited. This paper describes an ABM that addresses this topic, using data from the London Educational Authority's Junior Project. To compare the results and performance with more traditional modelling techniques, the same data are also fitted to a multilevel model (MLM), one of the preferred variable-based models used in the field. The paper reports the results of both models and compares their performances in terms of predictive and explanatory power. Although the fitted MLM outperforms the proposed ABM, the latter still offers a reasonable fit and provides a causal mechanism to explain differences in the identified school performances that is absent in the MLM. Since MLM and ABM stress different aspects, rather than conflicting they are compatible methods.

Fuzzy Logic for Social Simulation Using NetLogo

Luis R. Izquierdo, Doina Olaru, Segismundo S. Izquierdo, Sharon Purchase and Geoffrey N. Soutar
Journal of Artificial Societies and Social Simulation 18 (4) 1

Kyeywords: Fuzzy Logic, NetLogo, Social Simulation, Agent-Based Modelling, Mamdani Inference, IF-THEN Rule
Abstract: Fuzzy Logic is a framework particularly useful to formalise and deal with imprecise concepts and statements expressed in natural language. This paper has three related aims. First, it aims to provide a short introduction to the basics of Fuzzy Logic within the context of social simulation. Secondly, it presents a well-documented NetLogo extension that facilitates the use of Fuzzy Logic within NetLogo. Finally, by providing a concrete example, it shows how researchers can use the Fuzzy Logic extension to build agent-based models in which individual agents hold their own fuzzy concepts and use their own fuzzy rules, which may also change over time. We argue that Fuzzy Logic and the tools provided here can be useful in Social Simulation in different ways. For example, they can assist in the process of analysing the robustness of a certain social theory expressed in natural language to different specifications of the imprecise concepts that the theory may contain (such as e.g. “wealthy”, “poor” or “disadvantaged”). They can also facilitate the exploration of the effect that heterogeneity in concept interpretations may have in a society (i.e. the significance of the fact that different people may have different interpretations of the same concept). Thus, this paper and the tools included in it can make the endeavour of translating social theories into computer programs easier and more rigorous at the same time.

TreatMethHarm: An Agent-Based Simulation of How People Who Use Methamphetamine Access Treatment

Francois Lamy, Brendan Quinn, Robyn Dwyer, Nicola Thomson, David Moore and Paul Dietze
Journal of Artificial Societies and Social Simulation 19 (2) 3

Kyeywords: Agent-Based Modelling, Methamphetamine Use, Drug-Related Harms, Treatment Access, Drug Career
Abstract: Methamphetamine use in Australia has recently attracted considerable attention due to increased human and social costs. Despite evidences indicating increasing methamphetamine-related harm and significant numbers of frequent and dependent users, methamphetamine treatment coverage remains low in Australia. This paper aims to investigate the complex interplay between methamphetamine use and treatment-related access by designing an agent-based model, using epidemiological data and expert-derived assumptions. This paper presents the architecture and core mechanisms of an agent-based model, TreatMethHarm, and details the results of model calibration performed by testing the key model parameters. At this stage of development, TreatMethHarm is able to produce proportions of methamphetamine users that replicate those produced by our epidemiological survey. However, this agent-based model still requires additional information and further tests before validation. TreatMethHarm provides a useful tool to elicit dialogue between researchers from different disciplines, integrate a variety of data and identify missing information.

VALFRAM: Validation Framework for Activity-Based Models

Jan Drchal, Michal Čertický and Michal Jakob
Journal of Artificial Societies and Social Simulation 19 (3) 5

Kyeywords: Agent-Based Modelling, Activity Based Model, Transport, Validation, Methodology, Simulation
Abstract: Activity-based models are a specific type of agent-based models widely used in transport and urban planning to generate and study travel demand. They deal with agents that structure their behaviour in terms of daily activity schedules: sequences of activity instances (such as work, sleep or shopping) with assigned start times, durations and locations, and interconnected by trips with assigned transport modes and routes. Despite growing importance of activity-based models in transport modelling, there has been no work focusing specifically on statistical validation of such models so far. In this paper, we propose a six-step Validation Framework for Activity-based Models (VALFRAM) that exploits historical real-world data to quantify the model's validity in terms of a set of numeric metrics. The framework compares the temporal and spatial properties and the structure of modelled activity schedules against real-world origin-destination matrices and travel diaries. We demonstrate the usefulness of the framework on a set of six different activity-based transport models.

The Interplay Between Conformity and Anticonformity and its Polarizing Effect on Society

Patryk Siedlecki, Janusz Szwabiński and Tomasz Weron
Journal of Artificial Societies and Social Simulation 19 (4) 9

Kyeywords: Opinion Dynamics, Social Influence, Conformity, Anticonformity, Bi-Polarization, Agent-Based Modelling
Abstract: Simmering debates leading to polarization are observed in many domains. Although empirical findings show a strong correlation between this phenomenon and modularity of a social network, still little is known about the actual mechanisms driving communities to conflicting opinions. In this paper, we used an agent-based model to check if the polarization may be induced by a competition between two types of social response: conformity and anticonformity. The proposed model builds on the q-voter model (Castellano et al, 2009b) and uses a double-clique topology in order to capture segmentation of a community. Our results indicate that the interplay between intra-clique conformity and inter-clique anticonformity may indeed lead to a bi-polarized state of the entire system. We have found a dynamic phase transition controlled by the fraction L of negative cross-links between cliques. In the regime of small values of L the system is able to reach the total positive consensus. If the values of L are large enough, anticonformity takes over and the system always ends up in a polarized stated. Putting it the other way around, the segmentation of the network is not a sufficient condition for the polarization to appear. A suitable level of antagonistic interactions between segments is required to arrive at a polarized steady state within our model.

An Agent-Based Model of Electricity Consumer: Smart Metering Policy Implications in Europe

Julija Vasiljevska, Jochem Douw, Anna Mengolini and Igor Nikolic
Journal of Artificial Societies and Social Simulation 20 (1) 12

Kyeywords: Electricity Consumer, Agent-Based Modelling, Smart Metering, Consumer Values
Abstract: EU Regulation 2009/72/EC concerning common rules for internal market in electricity calls upon 80% of EU electricity consumers to be equipped with smart metering systems by 2020, provided that a positive economic assessment of all long-term costs and benefits to the market and the individual consumer is guaranteed. Understanding the impact that smart metering systems may have on the electricity stakeholders (consumers, distribution system operators, energy suppliers and the society at large) is important for faster and effective deployment of such systems and of the innovative services they offer. For this purpose, in this paper an agent-based model is developed, where the electricity consumer behaviour due to different smart metering policies is simulated. Consumers are modelled as household agents having dynamic preferences on types of electricity contracts offered by the supplier. Development of preferences depends on personal values, memory and attitudes, as well as the degree of interaction in a social network structure. We are interested in exploring possible diffusion rates of smart metering enabled services under different policy interventions and the impact of this technological diffusion on individual and societal performance indicators. In four simulation experiments and three intervention policies we observe the diffusion of energy services and individual and societal performance indicators (electricity savings, CO2 emissions savings, social welfare, consumers' comfort change), as well as consumers' satisfaction. From these results and based on expert validation, we conclude that providing the consumer with more options does not necessarily lead to higher consumer's satisfaction, or better societal performance. A good policy should be centred on effective ways to tackle consumers concerns.

An Agent-Based Model of Flood Risk and Insurance

Jan Dubbelboer, Igor Nikolic, Katie Jenkins and Jim Hall
Journal of Artificial Societies and Social Simulation 20 (1) 6

Kyeywords: Flooding, London, Flood Insurance, Flood Re, Agent-Based Modelling
Abstract: Flood risk emerges from the dynamic interaction between natural hazards and human vulnerability. Methods for the quantification of flood risk are well established, but tend to deal with human and economic vulnerability as being static or changing with an exogenously defined trend. In this paper we present an Agent-Based Model (ABM) developed to simulate the dynamical evolution of flood risk and vulnerability, and facilitate an investigation of insurance mechanism in London. The ABM has been developed to firstly allow an analysis of the vulnerability of homeowners to surface water flooding, which is one of the greatest short-term climate risks in the UK with estimated annual costs of £1.3bn to £2.2bn. These costs have been estimated to increase by 60-220% over the next 50 years due to climate change and urbanisation. Vulnerability is influenced by homeowner’s decisions to move house and/or install measures to protect their properties from flooding. In particular, the ABM focuses on the role of flood insurance, simulating the current public-private partnership between the government and insurers in the UK, and the forthcoming re-insurance scheme Flood Re, designed as a roadmap to support the future affordability and availability of flood insurance. The ABM includes interaction between homeowners, sellers and buyers, an insurer, a local government and a developer. Detailed GIS and qualitative data of the London borough of Camden are used to represent an area at high risk of surface water flooding. The ABM highlights how future development can exacerbate current levels of surface water flood risk in Camden. Investment in flood protection measures are shown to be beneficial for reducing surface water flood risk. The Flood Re scheme is shown to achieve its aim of securing affordable flood insurance premiums, however, is placed under increasing pressure in the future as the risk of surface water flooding continues to increase.

Agent-Based Modelling of Social-Ecological Systems: Achievements, Challenges, and a Way Forward

Jule Thober, Birgit Müller, Jürgen Groeneveld and Volker Grimm
Journal of Artificial Societies and Social Simulation 20 (2) 8

Kyeywords: Agent-Based Modelling, Social-Ecological Modelling, Model Development, Model Testing, Model Analysis, Human Decision-Making
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 potential of agent-based modelling for gaining general insights and supporting specific decision-making has already been utilized. We reviewed achievements and challenges by building upon developments in good modelling practice in the field of ecological modelling with its longer history. As a reference, we used the TRACE framework, which encompasses elements of model development, testing and analysis. We firstly reviewed achievements and challenges with regard to the elements of the TRACE framework addressed in reviews and method papers of social-ecological ABMs. Secondly, in a mini-review, we evaluated whether and to what degree the elements of the TRACE framework were addressed in publications on specific ABMs. We identified substantial gaps with regard to (1) communicating whether the models represented real systems well enough for their intended purpose and (2) analysing the models in a systematic and transparent way so that model output is not only observed but also understood. To fill these gaps, a joint effort of the modelling community is needed to foster the advancement and use of strategies such as participatory approaches, standard protocols for communication, sharing of source code, and tools and strategies for model design and analysis. Throughout our analyses, we provide specific recommendations and references for improving the state-of-the-art. We thereby hope to contribute to the establishment of a new advanced culture of agent-based modelling of SES that will allow us to better develop general theory and practical solutions.

Simulation for Interpretation: A Methodology for Growing Virtual Cultures

Ulf Lotzmann and Martin Neumann
Journal of Artificial Societies and Social Simulation 20 (3) 13

Kyeywords: Interpretative Research Process, Agent-Based Modelling, Generative Social Science, Qualitative Data, Thick Description, Cultural Studies
Abstract: Agent-based social simulation is well-known for generative explanations. Following the theory of thick description we extend the generative paradigm to interpretative research in cultural studies. Using the example of qualitative data about criminal culture, the paper describes a research process that facilitates interpretative research by growing virtual cultures. Relying on qualitative data for the development of agent rules, the research process combines several steps: Qualitative data analysis following the Grounded Theory paradigm enables concept identification, resulting in the development of a conceptual model of the concept relations. The software tool CCD is used in conceptual modelling which assists semi-automatic transformation in a simulation model developed in the simulation platform DRAMS. Both tools preserve traceability to the empirical evidence throughout the research process. Traceability enables interpretation of simulations by generating a narrative storyline of the simulation. Thereby simulation enables a qualitative exploration of textual data. The whole process generates a thick description of the subject of study, in our example criminal culture. The simulation is characterized by a socio-cognitive coupling of agents’ reasoning on the state of the mind of other agents. This reveals a thick description of how participants make sense of the phenomenology of a situation from the perspective of their worldview.

The Thin Blue Line Between Protesters and Their Counter-Protesters

Tamsin E. Lee
Journal of Artificial Societies and Social Simulation 21 (2) 10

Kyeywords: Agent-Based Modelling, Individual-Based Model, Protest Behaviour, Social Simulation, Netlogo
Abstract: More frequently protests are accompanied by an opposing group performing a counter protest. This phenomenon can increase tension such that police must try to keep the two groups separated. However, what is the best strategy for police? This paper uses a simple agent-based model to determine the best strategy for keeping the two groups separated. The 'thin blue line' varies in density (number of police), width and the keenness of police to approach protesters. Three different groups of protesters are modelled to mimic peaceful, average and volatile protests. In most cases, a few police forming a single-file 'thin blue line' separating the groups is very effective. However, when the protests are more volatile, it is more effective to have many police occupying a wide 'thin blue line', and police being keen to approach protesters. To the authors knowledge, this is the first paper to model protests and counter-protests.

Simulation of the Governance of Complex Systems (SimCo): Basic Concepts and Experiments on Urban Transportation

Fabian Adelt, Johannes Weyer, Sebastian Hoffmann and Andreas Ihrig
Journal of Artificial Societies and Social Simulation 21 (2) 2

Kyeywords: Governance, Agent-Based Modelling, Complexity, Infrastructure Systems, Transport Network, Transport Mode Choice
Abstract: The current paper is positioned at the intersection of computer simulation, governance research, and research on infrastructure systems, such as transportation or energy. It proposes a simulation framework, “Simulation of the governance of complex systems” (SimCo), to study the governability of complex socio-technical systems experimentally by means of agent-based modelling (ABM). SimCo is rooted in a sociological macro-micro-macro model of a socio-technical system, taking into account the interplay of agents' choices (micro) and situational constraints (macro). The paper presents the conceptualization of SimCo, its elements and subsystems as well as their interactions. SimCo depicts the daily routines of users performing their tasks (e.g. going to work) by choosing among different technologies (e.g. modes of transportation), occasionally deciding to replace a worn-out technology. All components entail different dimensions that can be adjusted, thus allowing operators to purposefully intervene, for instance in the case of risk management (e.g. preventing congestion) or system transformation (e.g. towards sustainable mobility). Experiments with a basic scenario of an urban road transport system demonstrate the effects of different modes of governance (soft control, strong control and a combination of both), revealing that soft control may be the best strategy to govern a complex socio-technical system.

PyNetLogo: Linking NetLogo with Python

Marc Jaxa-Rozen and Jan H. Kwakkel
Journal of Artificial Societies and Social Simulation 21 (2) 4

Kyeywords: Agent-Based Modelling, NetLogo, Python
Abstract: Methods for testing and analyzing agent-based models have drawn increasing attention in the literature, in the context of efforts to establish standard frameworks for the development and documentation of models. This process can benefit from the use of established software environments for data analysis and visualization. For instance, the popular NetLogo agent-based modelling software can be interfaced with Mathematica and R, letting modellers use the advanced analysis capabilities available in these programming languages. To extend these capabilities to an additional user base, this paper presents the pyNetLogo connector, which allows NetLogo to be controlled from the Python general-purpose programming language. Given Python’s increasing popularity for scientific computing, this provides additional flexibility for modellers and analysts. PyNetLogo’s features are demonstrated by controlling one of NetLogo’s example models from an interactive Python environment, then performing a global sensitivity analysis with parallel processing.

Agent-Based Modelling of Viticulture Development in Emerging Markets: The Case of the Małopolska Region

Marcin Czupryna, Paweł Oleksy, Piotr Przybek and Bogumił Kamiński
Journal of Artificial Societies and Social Simulation 21 (3) 6

Kyeywords: Agent-Based Modelling, Market Development, Behavioural Factors, Viticulture, Wine
Abstract: In this paper, we apply an agent-based approach to explain both the final state and the dynamics of the development process of the wine sector in the Małopolska region in Poland. This sector has been affected by various environmental, institutional, behavioural and social factors and has undergone evolutionary changes in recent years. The econometric analysis of empirical data of vineyards in this region provides insights into the degree of influence of various factors under consideration on the aggregate number of vineyards in sub-regions. However, this does no explain the dynamics of the local formation of new vineyards or the underlying latent attitudes of vineyard owners. To overcome this limitation, we developed an agent-based model with heterogeneous agents (regular farms as well as large and small vineyards), which allowed us to identify a two-stage development scenario: i) community building and ii) vineyard creation. Our findings are of two types. Firstly, we showed a case where the agent-based model has good predictive power, in situations where the econometric model fails. Secondly, estimation of the agent-based model parameters and sensitivity analysis revealed crucial factors that have driven development of viticulture in the Małopolska region. In particular, we find that the crucial element underlying the good predictive power of the model is that it enables us to capture the fact that wine enthusiasts initially concentrate in sub-regions with more benign environmental conditions. Next, when one of them eventually established a vineyard, agents in the community had a lowered barrier to entry via the possibility of practical knowledge exchange, joint marketing efforts or vineyard maintenance resource sharing. This is in line with current evidence, which shows strong clustering effects, namely, a relatively large number of vineyards originate at relatively similar times and locations.

How to Relate Models to Reality? An Epistemological Framework for the Validation and Verification of Computational Models

Claudius Graebner
Journal of Artificial Societies and Social Simulation 21 (3) 8

Kyeywords: Agent-Based Modelling, Epistemology, Models, Validation, Verification
Abstract: Agent-based simulations have become increasingly prominent in various disciplines. This trend is positive, but it comes with challenges: while there are more and more standards for design, verification, validation, and presentation of the models, the various meta-theoretical strategies of how the models should be related to reality often remain implicit. Differences in the epistemological foundations of models make it however, difficult to relate distinct models to each other and to ensure a cumulative expansion of knowledge. Concepts and the analytic language developed by philosophers of science can help to overcome these obstacles. This paper introduces some of these concepts to the modelling community. It also presents an epistemological framework that helps to clarify how one wishes to generate knowledge about reality by the means of one's model and that helps to relate models to each other. Since the interpretation of a model is strongly connected to the activities of model verification and validation, these two activities will be embedded into the framework and their respective epistemological roles will be clarified. The resulting meta-theoretical framework aligns well with recently proposed frameworks for model presentation and evaluation.

Explaining the Emerging Influence of Culture, from Individual Influences to Collective Phenomena

Loïs Vanhée and Frank Dignum
Journal of Artificial Societies and Social Simulation 21 (4) 11

Kyeywords: Cultures, Social Simulations, Agent-Based Modelling
Abstract: This paper presents a simulation model and derived from it a theory to explain how known cultural influences on individual decisions lead to collective phenomena. This simulation models the evolution of a business organization, replicating key micro-level cultural influences on individual decisions (such as allocating and accepting tasks) and subsequent macro-level collective cultural phenomena (such as robustness and sensitivity to environmental complexity). As a result, we derived a theory on how to relate the influence of culture from individual decisions to collective outcomes, based on this simulation. We also point out that cultures appear to be related to specific sets of abstract, coherent and recurrent interaction patterns between individuals.

Towards the Right Ordering of the Sequence of Models for the Evolution of a Population Using Agent-Based Simulation

Morgane Dumont, Johan Barthelemy, Nam Huynh and Timoteo Carletti
Journal of Artificial Societies and Social Simulation 21 (4) 3

Kyeywords: Microsimulation, Agent-Based Modelling, Ordering of Models, Population Evolution, Robustness
Abstract: Agent based modelling is nowadays widely used in transport and the social science. Forecasting population evolution and analysing the impact of hypothetical policies are often the main goal of these developments. Such models are based on sub-models defining the interactions of agents either with other agents or with their environment. Sometimes, several models represent phenomena arising at the same time in the real life. Hence, the question of the order in which these sub-models need to be applied is very relevant for simulation outcomes. This paper aims to analyse and quantify the impact of the change in the order of sub-models on an evolving population modelled using TransMob. This software simulates the evolution of the population of a metropolitan area in South East of Sydney (Australia). It includes five principal models: ageing, death, birth, marriage and divorce. Each possible order implies slightly different results mainly driven by how agents' ageing is defined with respect to death. Furthermore, we present a calendar-based approach for the ordering that decreases the variability of final populations. Finally, guidelines are provided proposing general advices and recommendations for researchers designing discrete time agent-based models.

Identifying Mechanisms Underlying Peer Effects on Multiplex Networks

Hang Xiong, Diane Payne and Stephen Kinsella
Journal of Artificial Societies and Social Simulation 21 (4) 6

Kyeywords: Peer Effects, Social Networks, Diffusion of Innovation, High-Value Crop
Abstract: We separately identify two mechanisms underlying peer effects in farm households' adoption of a new crop. A farmer can follow his peers to adopt a new crop because he learns knowledge about the new crop from them (social learning) and because he wants to avoid the damage caused by the practice conflicting with theirs (externalities). Using an agent-based model, we simulate the two mechanisms on a multiplex network consisting of two types of social relationships. The simulation model is estimated using detailed data of social networks, adoption and relevant socio-economic characteristics from 10 villages in China. We find that social learning -- in this case, the sharing of experiential resources -- among family members and production externalities between contiguous land plots both significantly influence farmers' adoption. Furthermore, sharing of experiential resources plays a significant role in the entire diffusion process and dominates the early phase, whereas externalities only matter in the late phase. This study shows the roles peer effects play in shaping diffusion can occur through different mechanisms and can vary as the diffusion proceeds. The work also suggests that agent-based models can help disentangle the role of social interactions in promoting or hindering diffusion.

Promoting Sustainable Food Consumption: An Agent-Based Model About Outcomes of Small Shop Openings

Roberto Calisti, Primo Proietti and Andrea Marchini
Journal of Artificial Societies and Social Simulation 22 (1) 2

Kyeywords: Sustainable Consumption, Agent-Based Modelling, Farmers’ Market, Consumer Behaviour, Consumer Networks, Location-Allocation Problem
Abstract: A useful way of promoting sustainable food consumption is to consider the spread of food retail operations focused on food diversification, food specialization, and fresh and local products. These food shops are generally small, which is a great problem for survival against ruthless competition from supermarkets. Our research objective was to construct a simulation with an agent-based model, reproducing the local food consumption market and to investigate how a new, small food retailing shop interacts with this market. As a case study, the model simulates the opening of a small farmers’ market. The intent of the model is to reproduce the current status of consumption for food products within a certain territorial context and given time period, and to investigate how consumers’ behaviour changes with the opening of the new shop. As a result, we could predict changes in consumers’ habits, the economic positioning of new, small shops and its best location. This information is of considerable interest for farmers’ markets and also for policymakers.

ABOOMS: Overcoming the Hurdles of Continuous-Time Public Goods Games with a Simulation-Based Approach

Tuong Manh Vu, Christian Wagner and Peer-Olaf Siebers
Journal of Artificial Societies and Social Simulation 22 (2) 7

Kyeywords: Agent-Based Modelling and Simulation, Continuous-Time Public Goods Game, Software Engineering, Agent-Based Computational Economics, Object-Oriented Analysis and Design
Abstract: Public Goods Games (PGGs) are a standard experimental economic approach to studying cooperative behaviour. There are two types of games: discrete-time and continuous-time PGGs. While discrete-time PGGs (one-shot decisions about contributions to public goods) can be easily done as lab experiments, continuous-time PGGs (where participants can change contributions at any time) are much harder to realise within a lab environment. This is mainly because it is difficult to consider events happening in continuous time in lab experiments. Simulation offers an opportunity to support real-world lab experiments and is well suited to explore continuous-time PGGs. In this paper, we show how to apply our recently developed ABOOMS (Agent-Based Object-Oriented Modelling and Simulation) development framework to create models for simulation-supported continuous-time PGG studies. The ABOOMS framework utilizes Software Engineering techniques to support the development at the macro level (considering the overall study lifecycle) and at the micro level (considering individual steps related to simulation model development). Our case study shows that outputs from the simulation-supported continuous-time PGG generate dynamics that do not exist in discrete-time setting, highlighting the fact that it is important to study both, discrete and continuous-time PGGs.

The Dynamics of Language Minorities: Evidence from an Agent-Based Model of Language Contact

Marco Civico
Journal of Artificial Societies and Social Simulation 22 (4) 3

Kyeywords: Language, Multilingualism, Minority, Complexity, Agent-Based Modelling, Population Dynamics
Abstract: This article discusses the adoption of a complexity theory approach to study the dynamics of language contact within multilingual communities. It develops an agent-based model that simulates the dynamics of communication within a community where a minority and a majority group coexist. The individual choice of language for communication is based on a number of simple rules derived from a review of the main literature on the topic of language contact. These rules are then combined with different variables, such as the rate of exogamy of the minority group and the presence of relevant education policies, to estimate the trends of assimilation of the minority group into the majority one. The model is validated using actually observed data from the case of Romansh speakers in the canton of Grisons, Switzerland. The data collected from the simulations are then analysed by means of regression techniques. This paper shows that macro-level language contact dynamics can be explained by relatively simple micro-level behavioural patterns and that intergenerational transmission is crucial for the long-term survival of minority-language groups.

An Innovative Approach to Multi-Method Integrated Assessment Modelling of Global Climate Change

Peer-Olaf Siebers, Zhi En Lim, Grazziela P. Figueredo and James Hey
Journal of Artificial Societies and Social Simulation 23 (1) 10

Kyeywords: Integrated Assessment Modelling, Climate Change, Agent-Based Modelling, System Dynamics Modelling, Methodological Advance, Hybridisation, Scalability
Abstract: Modelling and simulation play an increasingly significant role in exploratory studies for informing policy makers on climate change mitigation strategies. There is considerable research being done in creating Integrated Assessment Models (IAMs), which focus on examining the human impacts on climate change. Many popular IAMs are created as steady state optimisation models. They typically employ a nested structure of neoclassical production functions to represent the energy-economy system, holding aggregate views on variables, and hence are unable to capture a finer level of details of the underlying system components. An alternative approach that allows modelling populations as a collection of individual and unevenly distributed entities is Agent-Based Modelling, often used in the field of Social Simulation. But simulating huge numbers of individual entities can quickly become an issue, as it requires large amounts of computational resources. The goal of this paper is to introduce a conceptual framework for developing hybrid IAMs. This novel modelling approach allows us to reuse existing rigid, but well-established IAMs, and adds more flexibility by replacing aggregate stocks with a community of vibrant interacting entities. We provide a proof-of-concept of the application of this conceptual framework in form of an illustrative example. Our test case takes the settings of the US. It is solely created for the purpose of demonstrating our hybrid modelling approach; we do not claim that it has predictive powers.

How Policy Decisions Affect Refugee Journeys in South Sudan: A Study Using Automated Ensemble Simulations

Diana Suleimenova and Derek Groen
Journal of Artificial Societies and Social Simulation 23 (1) 2

Kyeywords: Refugee Modelling, Agent-Based Modelling, Automation Toolkit, Policy Decisions, Validation, Sensitivity Analysis
Abstract: Forced displacement has a huge impact on society today, as more than 68 million people are forcibly displaced worldwide. Existing methods for forecasting the arrival of migrants, especially refugees, may help us to better allocate humanitarian support and protection. However, few researchers have investigated the effects of policy decisions, such as border closures, on the movement of these refugees. Recently established simulation development approaches have made it possible to conduct such a study. In this paper, we use such an approach to investigate the effect of policy decisions on refugee arrivals for the South Sudan refugee crisis. To make such a study feasible in terms of human effort, we rely on agent-based modelling, and have automated several phases of simulation development using the FabFlee automation toolkit. We observe a decrease in the average relative difference from 0.615 to 0.499 as we improved the simulation model with additional information. Moreover, we conclude that the border closure and a reduction in camp capacity induce fewer refugee arrivals and more time spend travelling to other camps. While a border opening and an increase in camp capacity result in a limited increase in refugee arrivals at the destination camps. To the best of our knowledge, we are the first to conduct such an investigation for this conflict.

An Agent-Based Model of Firm Size Distribution and Collaborative Innovation

Inyoung Hwang
Journal of Artificial Societies and Social Simulation 23 (1) 9

Kyeywords: Agent-Based Modelling, Prisoner’s Dilemma, Pavlovian Cooperation, Collaborative Innovation, Firm Size Distribution, ICT Industry
Abstract: ICT-based Collaborative innovation has a significant impact on the economy by facilitating technological convergence and promoting innovation in other industries. However, research on innovation suggests that polarization in firm size distribution, which has grown since the early 2000s, can interfere with collaborative innovation among firms. In this paper, I modelled firms’ decision-making processes that led to collaborative innovation as a spatial N-person iterated Prisoner’s dilemma (NIPD) game using collaborative innovation data from Korean ICT firms. Using an agent-based model, I experimented with the effects of firm size heterogeneity on collaborative innovation. The simulation experiment results reveal that collaborative innovation in the industry increases as the size heterogeneity decreases. Findings suggest that policies promoting collaborative innovation should focus on mitigating structural inequalities in the industry.

A Software Architecture for Mechanism-Based Social Systems Modelling in Agent-Based Simulation Models

Tuong Manh Vu, Charlotte Probst, Alexandra Nielsen, Hao Bai, Petra S. Meier, Charlotte Buckley, Mark Strong, Alan Brennan and Robin C. Purshouse
Journal of Artificial Societies and Social Simulation 23 (3) 1

Kyeywords: Agent-Based Modelling, Social Simulation, Software Architecture, Analytical Sociology, Abductive Reasoning
Abstract: This paper introduces the MBSSM (Mechanism-Based Social Systems Modelling) software architecture that is designed for expressing mechanisms of social theories with individual behaviour components in a unified way and implementing these mechanisms in an agent-based simulation model. The MBSSM architecture is based on a middle-range theory approach most recently expounded by analytical sociology and is designed in the object-oriented programming paradigm with Unified Modelling Language diagrams. This paper presents two worked examples of using the architecture for modelling individual behaviour mechanisms that give rise to the dynamics of population-level alcohol use: a single-theory model of norm theory and a multi-theory model that combines norm theory with role theory. The MBSSM architecture provides a computational environment within which theories based on social mechanisms can be represented, compared, and integrated. The architecture plays a fundamental enabling role within a wider simulation model-based framework of abductive reasoning in which families of theories are tested for their ability to explain concrete social phenomena.

Simulating Crowds in Real Time with Agent-Based Modelling and a Particle Filter

Nick Malleson, Kevin Minors, Le-Minh Kieu, Jonathan A. Ward, Andrew West and Alison Heppenstall
Journal of Artificial Societies and Social Simulation 23 (3) 3

Kyeywords: Agent-Based Modelling, Particle Filter, Data Assimilation, Crowd Simulation, Pedestrian Modelling
Abstract: Agent-based modelling is a valuable approach for modelling systems whose behaviour is driven by the interactions between distinct entities, such as crowds of people. However, it faces a fundamental difficulty: there are no established mechanisms for dynamically incorporating real-time data into models. This limits simulations that are inherently dynamic, such as those of pedestrian movements, to scenario testing on historic patterns rather than real-time simulation of the present. This paper demonstrates how a particle filter could be used to incorporate data into an agent-based model of pedestrian movements at run time. The experiments show that although it is possible to use a particle filter to perform online (real time) model optimisation, the number of individual particles required (and hence the computational complexity) increases exponentially with the number of agents. Furthermore, the paper assumes a one-to-one mapping between observations and individual agents, which would not be the case in reality. Therefore this paper lays some of the fundamental groundwork and highlights the key challenges that need to be addressed for the real-time simulation of crowd movements to become a reality. Such success could have implications for the management of complex environments both nationally and internationally such as transportation hubs, hospitals, shopping centres, etc.

An Agent-Based Approach to Integrated Assessment Modelling of Climate Change

Marcin Czupryna, Christian Franzke, Sascha Hokamp and Jürgen Scheffran
Journal of Artificial Societies and Social Simulation 23 (3) 7

Kyeywords: Climate Change, Climate Protection, Integrated Assessment Model, Agent-Based Modelling
Abstract: There is an ongoing discussion concerning the relationship between social welfare and climate change, and thus the required level and type of measures needed to protect the climate. Integrated assessment models (IAMs) have been extended to incorporate technological progress, heterogeneity and uncertainty, making use of a (stochastic) dynamic equilibrium approach in order to derive a solution. According to the literature, the IAM class of models does not take all the relationships among economic, social and environmental factors into account. Moreover, it does not consider these interdependencies at the micro-level, meaning that all possible consequences are not duly examined. Here, we propose an agent-based approach to analyse the relationship between economic welfare and climate protection. In particular, our aim is to analyse how the decisions of individual agents, allowing for the trade-off between economic welfare and climate protection, influence the aggregated emergent economic behaviour. Using this model, we estimate a damage function, with values in the order 3% - 4%for 2 C temperature increase and having a linear (or slightly concave) shape. We show that the heterogeneity of the agents, technological progress and the damage function may lead to lower GDP growth rates and greater temperature-related damage than what is forecast by models with solely homogeneous (representative) agents.

Seed Selection Strategies for Information Diffusion in Social Networks: An Agent-Based Model Applied to Rural Zambia

Beatrice Nöldeke, Etti Winter and Ulrike Grote
Journal of Artificial Societies and Social Simulation 23 (4) 9

Kyeywords: Information Diffusion, Social Networks, Agent-Based Modelling, Seeding, Zambia
Abstract: The successful adoption of innovations depends on the provision of adequate information to farmers. In rural areas of developing countries, farmers usually rely on their social networks as an information source. Hence, policy-makers and program-implementers can benefit from social diffusion processes to effectively disseminate information. This study aims to identify the set of farmers who initially obtain information (‘seeds’) that optimises diffusion through the network. It systematically evaluates different criteria for seed selection, number of seeds, and their interaction effects. An empirical Agent-Based Model adjusted to a case study in rural Zambia was applied to predict diffusion outcomes for varying seed sets ex ante. Simulations revealed that informing farmers with the most connections leads to highest diffusion speed and reach. Also targeting village heads and farmers with high betweenness centrality, who function as bridges connecting different parts of the network, enhances diffusion. An increased number of seeds improves reach, but the marginal effects of additional seeds decline. Interdependencies between seed set size and selection criteria highlight the importance of considering both seed selection criteria and seed set size for optimising seeding strategies to enhance information diffusion.

Agent-Based Simulation of West Asian Urban Dynamics: Impact of Refugees

Ali Termos, Stefano Picascia and Neil Yorke-Smith
Journal of Artificial Societies and Social Simulation 24 (1) 2

Kyeywords: Rent-Gap Theory, Migration, Agent-Based Modelling, Urban Dynamics, Housing, Lebanon
Abstract: Rapid international migration of significant populations generates profound implications for countries in West Asia, Europe, and other regions. The motivation of this work is to develop an agent-based model (ABM) to capture the existence of such migrant and refugee flows, and to explore the effects of these flows on urban dynamics. Advances in agent-based modelling have led to theoretically-grounded spatial agent models of urban dynamics, capturing the dynamics of population, property prices, and regeneration. In this article we leverage such an extant agent-based model founded on the rent-gap theory, as a lens to study the effect of sizeable refugee migration upon a capital city in West Asia. In order to calibrate and validate the simulation model we construct indices for housing prices and other factors. Results from the model, implemented in NetLogo, show the impact of migration shock on the housing market, and identify the relative efficacy of housing intervention policies. Our work progresses towards a tool for policy makers asking what-if questions about the urban environment in the context of migration.

Justified Stories with Agent-Based Modelling for Local COVID-19 Planning

Jennifer Badham, Pete Barbrook-Johnson, Camila Caiado and Brian Castellani
Journal of Artificial Societies and Social Simulation 24 (1) 8

Kyeywords: Agent-Based Modelling, Epidemic, COVID-19, Descriptive Model, Social Distancing, Justified Stories
Abstract: This paper presents JuSt-Social, an agent-based model of the COVID-19 epidemic with a range of potential social policy interventions. It was developed to support local authorities in North East England who are making decisions in a fast moving crisis with limited access to data. The proximate purpose of JuSt-Social is description, as the model represents knowledge about both COVID-19 transmission and intervention effects. Its ultimate purpose is to generate stories that respond to the questions and concerns of local planners and policy makers and are justified by the quality of the representation. These justified stories organise the knowledge in way that is accessible, timely and useful at the local level, assisting the decision makers to better understand both their current situation and the plausible outcomes of policy alternatives. JuSt-Social and the concept of justified stories apply to the modelling of infectious disease in general and, even more broadly, modelling in public health, particularly for policy interventions in complex systems.

Cascades Across Networks Are Sufficient for the Formation of Echo Chambers: An Agent-Based Model

Jan-Philipp Fränken and Toby Pilditch
Journal of Artificial Societies and Social Simulation 24 (3) 1

Kyeywords: Echo Chambers, Source Credibility, Information Cascades, Agent-Based Modelling, Bayesian Modelling, Single Interaction
Abstract: Investigating how echo chambers emerge in social networks is increasingly crucial, given their role in facilitating the retention of misinformation, inducing intolerance towards opposing views, and misleading public and political discourse. Previously, the emergence of echo chambers has been attributed to psychological biases and inter-individual differences, requiring repeated interactions among network-users and rewiring or pruning of social ties. Using an idealised population of social network users, the present results suggest that when combined with positive credibility perceptions of a communicating source, social media users’ ability to rapidly share information with each other through a single cascade can be sufficient to produce echo chambers. Crucially, we show that this requires neither special psychological explanation (e.g., bias or individual differences), nor repeated interactions—though these may be exacerbating factors. In fact, this effect is made increasingly worse the more generations of peer-to-peer transmissions it takes for information to permeate a network. This raises important questions for social network architects, if truly opposed to the increasing prevalence of deleterious societal trends that stem from echo chamber formation.

Using Agent-Based Models for Prediction in Complex and Wicked Systems

J. Gareth Polhill, Matthew Hare, Tom Bauermann, David Anzola, Erika Palmer, Doug Salt and Patrycja Antosz
Journal of Artificial Societies and Social Simulation 24 (3) 2

Kyeywords: Prediction, Complex Systems, Wicked Systems, Agent-Based Modelling, Cellular Automata, Turing Machines
Abstract: This paper uses two thought experiments to argue that the complexity of the systems to which agent-based models (ABMs) are often applied is not the central source of difficulties ABMs have with prediction. We define various levels of predictability, and argue that insofar as path-dependency is a necessary attribute of a complex system, ruling out states of the system means that there is at least the potential to say something useful. ‘Wickedness’ is argued to be a more significant challenge to prediction than complexity. Critically, however, neither complexity nor wickedness makes prediction theoretically impossible in the sense of being formally undecidable computationally-speaking: intractable being the more apt term given the exponential sizes of the spaces being searched. However, endogenous ontological novelty in wicked systems is shown to render prediction futile beyond the immediately short term.

Actor Behaviour and Robustness of Industrial Symbiosis Networks: An Agent-Based Modelling Approach

Kasper Lange, Gijsbert Korevaar, Igor Nikolic and Paulien Herder
Journal of Artificial Societies and Social Simulation 24 (3) 8

Kyeywords: Circular Economy, Industrial Symbiosis, Cooperative Networks, Agent-Based Modelling, Theory of Planned Behaviour, Eco-Oriented Behaviour
Abstract: Industrial Symbiosis Networks (ISNs) consist of firms that exchange residual materials and energy locally, in order to gain economic, environmental and/or social advantages. In practice, ISNs regularly fail when partners leave and the recovery of residual streams ends. Regarding the current societal need for a shift towards sustainability, it is undesirable that ISNs should fail. Failures of ISNs may be caused by actor behaviour that leads to unanticipated economic losses. In this paper, we explore the effect of these behaviours on ISN robustness by using an agent-based model (ABM). The constructed model is based on insights from both literature and participatory modelling in three real-world cases. It simulates the implementation of synergies for local waste exchange and compost production. The Theory of Planned Behaviour (TPB) was used to model agent behaviour in time-dependent bilateral negotiations and synergy evaluation processes. We explored model behaviour with and without TPB logic across a range of possible TPB input variables. The simulation results show how the modelled planned behaviour affects the cash flow outcomes of the social agents and the robustness of the network. The study contributes to the theoretical development of industrial symbiosis research by providing a quantitative model of all ISN implementation stages, in which various behavioural patterns of entrepreneurs are included. It also contributes to practice by offering insights on how network dynamics and robustness outcomes are not only related to context and ISN design, but also to actor behaviour.

Comparing Mechanisms of Food Choice in an Agent-Based Model of Milk Consumption and Substitution in the UK

Matthew Gibson, Raphael Slade, Joana Portugal Pereira and Joeri Rogelj
Journal of Artificial Societies and Social Simulation 24 (3) 9

Kyeywords: Food Choice, Milk Consumption, Consumer Behaviour, Agent-Based Modelling, Calibration Optimisation, Global Temporal Sensitivity Analysis
Abstract: Substitution of food products will be key to realising widespread adoption of sustainable diets. We present an agent-based model of decision-making and influences on food choice, and apply it to historically observed trends of British whole and skimmed (including semi) milk consumption from 1974 to 2005. We aim to give a plausible representation of milk choice substitution, and test different mechanisms of choice consideration. Agents are consumers that perceive information regarding the two milk choices, and hold values that inform their position on the health and environmental impact of those choices. Habit, social influence and post-decision evaluation are modelled. Representative survey data on human values and long-running public concerns empirically inform the model. An experiment was run to compare two model variants by how they perform in reproducing these trends. This was measured by recording mean weekly milk consumption per person. The variants differed in how agents became disposed to consider alternative milk choices. One followed a threshold approach, the other was probability based. All other model aspects remained unchanged. An optimisation exercise via an evolutionary algorithm was used to calibrate the model variants independently to observed data. Following calibration, uncertainty and global variance-based temporal sensitivity analysis were conducted. Both model variants were able to reproduce the general pattern of historical milk consumption, however, the probability-based approach gave a closer fit to the observed data, but over a wider range of uncertainty. This responds to, and further highlights, the need for research that looks at, and compares, different models of human decision-making in agent-based and simulation models. This study is the first to present an agent-based modelling of food choice substitution in the context of British milk consumption. It can serve as a valuable pre-curser to the modelling of dietary shift and sustainable product substitution to plant-based alternatives in Britain.

The Dynamical Relation Between Individual Needs and Group Performance: A Simulation of the Self-Organising Task Allocation Process

Shaoni Wang, Kees Zoethout, Wander Jager and Yanzhong Dang
Journal of Artificial Societies and Social Simulation 24 (4) 9

Kyeywords: Individual Needs, Motivation, Group Performance, Self-Organisation, Task Allocation, Agent-Based Modelling
Abstract: Team performance can be considered a macro-level outcome that depends on three sets of micro-level factors: individual workers contributing to the task, team composition, and task characteristics. For a number of reasons, the complex dynamics between individuals in the task allocation process are difficult to systematically explore in traditional experimental settings: the motivational dynamics, the complex dynamics of task allocation processes, and the lack of experimental control over team composition imply an ABM-approach being more feasible. For this reason, we propose an updated version of the WORKMATE model that has been developed to explore the dynamics of team performance. In doing so, we added Deci and Ryan’s SDT theory, stating that people are motivated by three psychological needs, competence, autonomy, and belongingness. This paper is aimed at explaining the architecture of the model, and some first simulation runs as proof of concept. The experimental results show that: 1) an appropriate motivation threshold will help the team have the lowest performance time; 2) the time needed for the task allocation process is related to the importance of different motivations; 3) highly satisfied teams are more likely composed of members valuing autonomy.

A Comparative Study on Apprenticeship Systems Using Agent-Based Simulation

Amir Hosein Afshar Sedigh, Martin Purvis, Tony Bastin Roy Savarimuthu, Christopher Konstantin Frantz and Maryam Purvis
Journal of Artificial Societies and Social Simulation 25 (1) 1

Kyeywords: Apprenticeship, Agent-Based Modelling, Social Simulations, Comparative Systems, Institutions, Historical Systems
Abstract: In this paper, we investigate the effects of different characteristics of apprenticeship programmes both in historical and contemporary societies. Apprenticeship is one of the major means to transfer skills in a society. We consider five societies: the Old Britain system (AD 1300s−1600s), the British East India Company (AD 1600s − 1800s), Armenian merchants of New-Julfa (AD 1600s − 1700s), contemporary German apprenticeship (1990s), and the “Modern Apprenticeship” in Britain (2001). In comparing these systems, using an agent-based simulation model, we identified six characteristics which impact the success of an apprenticeship programme in a society, which we measured by considering three parameters, namely the number of skilled agents produced by the apprenticeships, programme completion, and the contribution of programmes to the Gross Domestic Income (GDI) of the society. We investigate different definitions for success of an apprenticeship and some hypothetical societies to test some common beliefs about apprenticeships' performance. The simulations suggest that a) it is better to invest in a public educational system rather than subsidising private contractors to train apprentices, b) having a higher completion ratio for apprenticeship programme does not necessarily result in a higher contribution in the GDI, and c) governors (e.g. mayors or government) that face significant emigration should also consider employing policies that persuade apprentices to complete their programme and stay in the society after completion to improve apprenticeship efficacy.

Multimodal Evolutionary Algorithms for Easing the Complexity of Agent-Based Model Calibration

Juan Francisco Robles, Enrique Bermejo, Manuel Chica and Óscar Cordón
Journal of Artificial Societies and Social Simulation ()

Kyeywords: Agent-Based Modelling, Model Validation, Automatic Calibration, Multimodal Optimisation, Multimodal Evolutionary Algorithms
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 analyse the performance of each multimodal evolutionary algorithm on 12 problem instances of an agent-based model for marketing (i.e. 12 different virtual markets) where we calibrate 24 to 129 parameters to generate two main outputs: historical brand awareness and word-of-mouth volume. Our study shows a clear dominance of SHADE, L-SHADE, and NichePSO over the rest of the multimodal evolutionary algorithms. We also highlight the benefits of these methods for helping modellers to choose from among the best calibrated solutions.