73 articles matched your search for
JASSS, Social Simulation, Bibliometric Analysis, Impact, Inter-Journal Citations
Journal of Artificial Societies and Social Simulation 1 (2) 4
Kyeywords: Agent Based Models (ABM), Chaos, Intelligent Agents, Social Simulation, Swarm
Abstract: Social scientists are not computer scientists, but their skills in the field have to become better and better to cope with the growing field of social simulation and agent based modelling techniques. A way to reduce the weight of software development is to employ generalised agent development tools, accepting both the boundaries necessarily existing in the various packages and the subtle and dangerous differences existing in the concept of agent in computer science, artificial intelligence and social sciences. The choice of tools based on the object oriented paradigm that offer libraries of functions and graphic widgets is a good compromise. A product with this kind of capability is Swarm, developed at the Santa Fe Institute and freely available, under the terms of the GNU license. A small example of a model developed in Swarm is introduced, in order to show directly the possibilities arising from the use of these techniques, both as software libraries and methodological guidelines. With simple agents - interacting in a Swarm context to solve both memory and time simulation problems - we observe the emergence of chaotic sequences of transaction prices.
Journal of Artificial Societies and Social Simulation 2 (1) 3
Kyeywords: Multi-Level Simulation, Social Simulation, Lisp, Computer Modelling, Social Simulation Tookit
Abstract: A package of Lisp functions is described which implements a simple multi-level simulation toolkit, MLS. Its design owes a great deal to MIMOSE. MLS runs within Lisp-Stat. It offers a set of functions, macros and objects designed to make the specification of multi-level models straightforward and easy to understand. Lisp-Stat provides a Lisp environment, statistical functions and easy to use graphics, such as histograms, scatterplots and spin-plots, to make the results of multi-level simulations easy to visualise.
Rosaria Conte and Scott Moss
Journal of Artificial Societies and Social Simulation 2 (1) 4
Kyeywords: Agent-Based Social Simulation, Special Interest Group, AgentLink
Journal of Artificial Societies and Social Simulation 3 (2) 1
Kyeywords: Complex Systems, Autopoiesis, Social Simulation, Cognition, Agents, Modelling. Meta-Model, Ontology
Abstract: There is growing interest in extending complex systems approaches to the social sciences. This is apparent in the increasingly widespread literature and journals that deal with the topic and is being facilitated by adoption of multi-agent simulation in research. Much of this research uses simple agents to explore limited aspects of social behaviour. Incorporation of higher order capabilities such as cognition into agents has proven problematic. Influenced by AI approaches, where cognitive capability has been sought, it has commonly been attempted based on a 'representational' theory of cognition. This has proven computationally expensive and difficult to implement. There would be some benefit also in the development of a framework for social simulation research which provides a consistent set of assumptions applicable in different fields and which can be scaled to apply to simple and more complex simulation tasks. This paper sets out, as a basis for discussion, a meta-model incorporating an 'enactive' model of cognition drawing on both complex system insights and the theory of autopoiesis. It is intended to provide an ontology that avoids some of the limitation of more traditional approaches and at the same time providing a basis for simulation in a wide range of fields and pursuant of a wider range of human behaviours.
Wolfgang Balzer, Karl R. Brendel and Solveig Hofmann
Journal of Artificial Societies and Social Simulation 4 (2) 1
Kyeywords: Social Simulation, Game Theory, Discrete Event Simulation, Model Theory, Confirmation, Impossibility Theorem
Abstract: The aim of this note is to clarify and to correct some arguments which are used in the debate about the comparison of discrete social simulation with other methodologies used in the study of social phenomena, notably those of game theory. Though part of what will be said also applies to non-discrete simulation, the arguments are investigated only as far as the discrete case is concerned. The main claims against each of both scientific approaches are considered in particular, i.e. "impossibility" of game theory and "unsoundness" of simulation studies. Regarding the latter, arguments are presented that items occurring in simulation studies correspond to the formal constituents of a scientific theory, and thus a comparison of both approaches on the same level is justified. The question whether a superiority of one of the two approaches can be stated is illuminated in the light of four dimensions: empirical adequacy, theoretical fruitfulness, social relevance, and simplicity. This leads to the conclusion that both claims are unjustified and should be avoided in the debate about the role and merits of social simulation.
Marie-Edith Bissey and Guido Ortona
Journal of Artificial Societies and Social Simulation 5 (2) 2
Kyeywords: Cooperation, Conventions, Prisoner's Dilemma, Social Simulation, SWARM
Abstract: This paper describes a study of the robustness of cooperative conventions. We observe the effect of the invasion of non-cooperating subjects into a community adopting a cooperative convention. The convention is described by an indefinitely repeated prisoner-dilemma game. We check the effects on the robustness of the cooperating convention of two characteristics of the game, namely the size of the prisonner-dilemma groups and the "intelligence" of the players. The relevance for real-world problems is considered. We find that the "intelligence" of the players plays a crucial role in the way players learn to cooperate. The simulation program is written in SWARM (Java version).
John Scott and Scott Moss
Journal of Artificial Societies and Social Simulation 5 (3) 9
Kyeywords: European Social Simulation Association, development of social simulation research, education and application.
Abstract: There is growing agreement that the time has come to form a learned society to promote the development of social simulation. The undersigned wish to propose the formation of a European Social Simulation Association (ESSA). Recognising parallel interests and developments in North America, Latin America and Australasia, we would intend ESSA to coordinate with similar organisations in those and other regions to organise an international federation to support the development of social simulation research, education and application.
Claudia Pahl-Wostl and Eva Ebenhöh
Journal of Artificial Societies and Social Simulation 7 (1) 3
Kyeywords: Social Simulation, Experimental Economics, Common Pool Resource Games, Adaptive Toolbox, Altruistic Punishment
Abstract: This article describes a social simulation model based on an economic experiment about altruistic behavior. The experiment by Fehr and Gächter showed that participants made frequent use of costly punishment in order to ensure continuing cooperation in a common pool resource game. The model reproduces not only the aggregated but also the individual data from the experiment. It was based on the data rather than theory. By this approach new insights about human behaviour and decision making may be found. The model was not designed as a stand-alone model, but as a starting point for a comprehensive Adaptive Toolbox Model. This may form a framework for modelling results from different economic experiments, comparing results and underlying assumptions, and exploring whether the insights thus gained also apply to more realistic situations.
Journal of Artificial Societies and Social Simulation 7 (2) 8
Kyeywords: Simulation, Modeling, Terrorism, Discrete Event, Agent-Oriented, Social Simulation, Soft Systems
Abstract: A discrete-event model of the dynamics of certain social structures is presented. The structures include terrorist organizations, anti-terrorism and terrorism-supporting structures. The simulation shows the process of creating the structures and their interactions. As a result, we can see how the structure size changes and how the interactions work, and the process of destroying terrorist organization links by the anti-terrorist agents. The simulation is agent-oriented and uses the PASION simulation system.
Journal of Artificial Societies and Social Simulation 7 (4) 4
Kyeywords: Formal Logic, Social Interaction, Social Simulation, Agents, Social Meta-Reasoning, Reasoning About Reasoning
Abstract: Formal logic has become an invaluable tool for research on multi-agent systems, but it plays a minor role in the more applied field of agent-based social simulation (ABSS). We argue that logical languages are particularly useful for representing social meta-reasoning, that is, agents' reasoning about the reasoning of other agents. After arguing that social meta-reasoning is a frequent and important social phenomenon, we present a set of general criteria (functional completeness, understandability, changeability, and implementability/executability) to compare logic to two alternative formal methods: black box techniques (e.g., neural networks) and decision-theoretical models (e.g., game theory). We then argue that in terms of functional completeness, understandability and changeability, logical representations of social meta-reasoning compare favorably to these two alternatives.
Journal of Artificial Societies and Social Simulation 7 (4) 5
Kyeywords: Methodology, Modelling, Social Simulation, MABS, Theory, Philosophy
Abstract: This paper suggests procedures for decreasing misunderstanding between modellers in social simulation, aiming at helping modellers comprehending a certain phenomena from different perspectives, being aware of the relativity of each approach, and drawing conclusions from the different perspectives. A hierarchy of four levels of language, namely, cultural or natural language, modelling and theoretical paradigm, modelling language, and simulation programming language, is proposed and exemplified as a framework for examining simulation models - assumptions of language embedded in the model at each level are made explicit. Afterwards, switching between languages is suggested for achieving different interpretations and alternative explanations of a model; alongside, as a synthesis from different interpretations, to draw in an interpretive conclusion is suggested. In addition, Interpretive Systemology, a soft systems approach, is proposed as another innovative alternative for better understanding social simulation models, as it recommends undertaking the whole modelling process from different perspectives. The hierarchy of languages, and switching between languages, will be placed against the whole modelling process as understood by Edmonds (2000).
Johannes Kottonau and Claudia Pahl-Wostl
Journal of Artificial Societies and Social Simulation 7 (4) 6
Kyeywords: Attitude Formation, Social Simulation, Voting Behavior
Abstract: Understanding the dynamics of attitude formation is a key issue in social psychology. The paper presents a computational model for simulating the formation and change of attitudes and the influence of the strength of attitudes on behavior. The main conceptual challenge was to capture not only the traditional attitude concept but the full concept of attitude strength. This required combining different theoretical approaches within an integrated modeling framework. The dynamics of political attitudes of German citizens were chosen as specific application area because of the considerable amount of empirical data available. The model was tested by simulating the effects of different voting campaign strategies on the outcome of an election. Uncertainties in model parameters were accounted for by using Monte Carlo simulations. The implications of specific theoretical assumptions were investigated by performing model simulations for different model structures. The paper shows the potential of social simulation when it comes to bringing together different theoretical approaches. The integration within a model exposes gaps and inconsistencies and allows formulating hypotheses for further empirical investigations. The model has a modular structure and provides a rich repository for other modelers who are working in the field of attitude simulation.
Pieter Buzing, A.E. Eiben and Martijn C. Schut
Journal of Artificial Societies and Social Simulation 8 (1) 2
Kyeywords: Social Simulation, Communication, Cooperation, Artificial Societies
Abstract: The main contribution of this paper is threefold. First, it presents a new software system for empirical investigations of evolving agent societies in SugarScape like environments. Second, it introduces a conceptual framework for modeling cooperation in an artificial society. In this framework the environmental pressure to cooperate is controllable by a single parameter, thus allowing systematic investigations of system behavior under varying circumstances. Third, it reports upon results from experiments that implemented and tested environments based upon this new model of cooperation. The results show that the pressure to cooperate leads to the evolution of communication skills facilitating cooperation. Furthermore, higher levels of cooperation pressure lead to the emergence of increased communication.
Shah Jamal Alam, Frank Hillebrandt and Michael Schillo
Journal of Artificial Societies and Social Simulation 8 (3) 5
Kyeywords: Gift Exchange, Multiagent Systems, Habitus-Field Theory, Social Simulation
Abstract: In this paper, the implications of applying the idea of gift exchange mechanism, inspired from Pierre Bourdieu's sociological theories, into a market-based multiagent system are explored. Our work is directed in the continuation of investigations by Knabe (2002), who addressed the formation of different organizations structures between providers in a profit-oriented market. We nevertheless scrutinize various hypotheses centered to gift exchange in which an agent sacrifices its profit for a long-term binding relationship. The idea is to aim a larger profit through alliances that are formed as an effect of gift exchange. Our suggestion is that a multiagent system (MAS) based on the social mechanism of gift exchange performs a high level of robustness and durability. The market in our case comprises of customers and providers agents. The former calls for proposals for the tasks they introduce in the market, while the latter proceed with the execution of tasks based on their abilities and other circumstances. In well defined cases, the providers are able to delegate tasks to other providers. This allows them to give presents to other providers so that the gift exchange mechanism becomes possible. The agents are either profit-oriented or the ones who prefer exchanging gifts and are in pursuit of others who also practice this mechanism. A number of interesting scenarios are examined that include preservation of a hierarchical structure in the market, situations resulting in the forming of an alliance between two providers, and split of profit-oriented and gift-giving agents.
Scott Moss and Bruce Edmonds
Journal of Artificial Societies and Social Simulation 8 (4) 13
Kyeywords: Methodology, Agent Based Social Simulation, Qualitative Analysis; Evidence; Conditions of Application; History of Science
Abstract: The paper investigates what is meant by "good science" and "bad science" and how these differ as between the natural (physical and biological) sciences on the one hand and social sciences on the other. We conclude on the basis of historical evidence that the natural science are much more heavily constrained by evidence and observation than by theory while the social sciences are constrained by prior theory and hardly at all by direct evidence. Current examples of the latter proposition are taken from recent issues of leading social science journals. We argue that agent based social simulations can be used as a tool to constrain the development of a new social science by direct (what economists dismiss as anecdotal) evidence and that to do so would make social science relevant to the understanding and influencing of social processes. We argue that such a development is both possible and desirable. We do not argue that it is likely.
Petra Ahrweiler and Nigel Gilbert
Journal of Artificial Societies and Social Simulation 8 (4) 14
Kyeywords: Evaluation, Social Simulation, Standard View, Constructivist View, User Community
Abstract: This contribution deals with the assessment of the quality of a simulation by discussing and comparing "real-world" and scientific social simulations. We use the example of the Caffè Nero in Guildford as a 'real-world' simulation of a Venetian café. The construction of everyday simulations like Caffè Nero has some resemblance to the construction procedure of scientific social simulations. In both cases, we build models from a target by reducing the characteristics of the latter sufficiently for the purpose at hand; in each case, we want something from the model we cannot achieve easily from the target. After briefly discussing the 'ordinary' method of evaluating simulations called the 'standard view' and its adversary, a constructivist approach asserting that 'anything goes', we heed these similarities in the construction process and apply evaluation methods typically used for everyday simulations to scientific simulation and vice versa. The discussion shows that a 'user community view' creates the foundation for every evaluation approach: when evaluating the Caffè Nero simulation, we refer to the expert community (customers, owners) who use the simulation to get from it what they would expect to get from the target; similarly, for science, the foundation of every validity discussion is the ordinary everyday interaction that creates an area of shared meanings and expectations. Therefore, the evaluation of a simulation is guided by the expectations, anticipations and experience of the community that uses it – for practical purposes (Caffè Nero), or for intellectual understanding and for building new knowledge (science simulation).
Guillaume Deffuant, Scott Moss and Wander Jager
Journal of Artificial Societies and Social Simulation 9 (1) 1
Kyeywords: Social Simulations, Epistemology, Validation, Simulation Methods
Abstract: The paper relates virtual dialogues about social simulation, with the implicit reference to Galieo\'s \'dialogues concerning two new sciences\'.
Journal of Artificial Societies and Social Simulation 9 (2) 8
Kyeywords: Social Simulation, Economic Theory, User Community
Abstract: This paper presents the analysis of a dataset of publications in economics that makes use of simulations. Data areas explored in order to obtain information about diffusion of simulation techniques in time and across sub-disciplines. Moreover, following Robert Axelrod\'s concerns about the difficulties in sharing simulation models and their outputs, some peculiarities in the communication process among \'simulators\' are highlighted.
Thomas Malsch and Ingo Schulz-Schaeffer
Journal of Artificial Societies and Social Simulation 10 (1) 11
Kyeywords: Socionics, Sociology, Multi-Agent Systems, Artificial Social Systems, Hybrid Systems, Social Simulation
Abstract: Socionics is an interdisciplinary approach with the objective to use sociological knowledge about the structures, mechanisms and processes of social interaction and social communication as a source of inspiration for the development of multi-agent systems, both for the purposes of engineering applications and of social theory construction and social simulation. The approach has been spelled out from 1998 on within the Socionics priority program funded by the German National research foundation. This special issue of the JASSS presents research results from five interdisciplinary projects of the Socionics program. The introduction gives an overview over the basic ideas of the Socionics approach and summarizes the work of these projects.
Klaus Jaffe and Roberto Cipriani
Journal of Artificial Societies and Social Simulation 10 (1) 7
Kyeywords: Social Simulation, Interactions, Group Size, Selfish Heard, Cultural Evolution, Biological Evolution
Abstract: A one dimensional cellular automata model describes the evolutionary dynamics of cooperation when grouping by cooperators provides protection against predation. It is used to compare the dynamics of evolution of cooperation in three settings. G: only vertical transmission of information is allowed, as an analogy of genetic evolution with heredity; H: only horizontal information transfer is simulated, through diffusion of the majority\'s opinion, as an analogy of opinion dynamics or social learning; and C: analogy of cultural evolution, where information is transmitted both horizontally (H) and vertically (V) so that learned behavior can be transmitted to offspring. The results show that the prevalence of cooperative behavior depends on the costs and benefits of cooperation so that: a- cooperation becomes the dominant behavior, even in the presence of free-riders (i.e., non-cooperative obtaining benefits from the cooperation of others), under all scenarios, if the benefits of cooperation compensate for its cost; b- G is more susceptible to selection pressure than H achieving a closer adaptation to the fitness landscape; c- evolution of cooperative behavior in H is less sensitive to the cost of cooperation than in G; d- C achieves higher levels of cooperation than the other alternatives at low costs, whereas H does it at high costs. The results suggest that a synergy between H and V is elicited that makes the evolution of cooperation much more likely under cultural evolution than under the hereditary kind where only V is present.
J. Gareth Polhill, Edoardo Pignotti, Nicholas M. Gotts, Pete Edwards and Alun Preece
Journal of Artificial Societies and Social Simulation 10 (2) 2
Kyeywords: Agent-Based Social Simulation, Experiments, Ontologies, Replication, Semantic Grid
Abstract: Agent-based models, perhaps more than other models, feature large numbers of parameters and potentially generate vast quantities of results data. This paper shows through the FEARLUS-G project (an ESRC e-Social Science Initiative Pilot Demonstrator Project) how deploying an agent-based model on the Semantic Grid facilitates international collaboration on investigations using such a model, and contributes to establishing rigorous working practices with agent-based models as part of good science in social simulation. The experimental workflow is described explicitly using an ontology, and a Semantic Grid service with a web interface implements the workflow. Users are able to compare their parameter settings and results, and relate their work with the model to wider scientific debate.
J. Gareth Polhill and Bruce Edmonds
Journal of Artificial Societies and Social Simulation 10 (3) 10
Kyeywords: Agent-Based Social Simulation, Replication, Software Licences, Documentation, Archiving
Abstract: We consider here issues of open access to social simulations, with a particular focus on software licences, though also briefly discussing documentation and archiving. Without any specific software licence, the default arrangements are stipulated by the Berne Convention (for those countries adopting it), and are unsuitable for software to be used as part of the scientific process (i.e. simulation software used to generate conclusions that are to be considered part of the scientific domain of discourse). Without stipulating any specific software licence, we suggest rights that should be provided by any candidate licence for social simulation software, and provide in an appendix an evaluation of some popularly used licences against these criteria.
Onofrio Gigliotta, Orazio Miglino and Domenico Parisi
Journal of Artificial Societies and Social Simulation 10 (4) 1
Kyeywords: Agent Based Models, Leaders, Social Simulation, Social Structure, Communication Topologies
Abstract: We describe simulations of groups of agents that have to reach a target in a two dimensional environment, the performance criterion being the time taken by the last agent to reach the target. If the target is within a given distance from the agent, the agent moves towards the target; otherwise it moves randomly. The simulations contrast groups with and without a leader, where a leader is a member of the group which other members of the group follow as it moves through the environment. We investigate three factors that affect group performance: (1) group size; (2) the presence or absence of an individual agent with the ability to detect targets at a greater distance than those \'visible\' to its companions; (3) the existence of a communication network among group members. The results show that, in groups without communication, leaders have a beneficial effect on group performance, especially in large groups and if the individual with better than average sensory capabilities is the leader of the group. However, in situations where group members can communicate, these results are reversed, with leaders being detrimental, rather than beneficial, to group performance
Minh Nguyen-Duc and Alexis Drogoul
Journal of Artificial Societies and Social Simulation 10 (4) 5
Kyeywords: Participatory Social Simulations, Agent-Based Social Simulations, Computational Agents, Role-Playing Games, Artificial Maieutics, User-Centered Design
Abstract: In social science, the role of stakeholders is increasing in the development and use of simulation models. Their participation in the design of agent-based models (ABMs) has widely been considered as an efficient solution to the validation of this particular type of model. Traditionally, "agents" (as basic model elements) have not been concerned with stakeholders directly but via designers or role-playing games (RPGs). In this paper, we intend to bridge this gap by introducing computational or software agents, implemented from an initial ABM, into a new kind of RPG, mediated by computers, so that these agents can interact with stakeholders. This interaction can help not only to elicit stakeholders' informal knowledge or unpredicted behaviours, but also to control stakeholders' focus during the games. We therefore formalize a general participatory design method using software agents, and illustrate it by describing our experience in a project aimed at developing agent-based social simulations in the field of air traffic management.
Shah Jamal Alam, Ruth Meyer, Gina Ziervogel and Scott Moss
Journal of Artificial Societies and Social Simulation 10 (4) 7
Kyeywords: Agent-Based Social Simulation, Evidence-Driven Modeling, Socioeconomic Stressors, HIV/AIDS Impact
Abstract: In this paper, we present an agent-based simulation model of the social impacts of HIV/AIDS in villages in the Sekhukhune district of the Limpopo province in South Africa. AIDS is a major concern in South Africa, not just in terms of disease spread but also in term of its impact on society and economic development. The impact of the disease cannot however be considered in isolation from other stresses, such as food insecurity, high climate variability, market fluctuations and variations in support from government and non-government sources. The model described in this paper focuses on decisions made at the individual and household level, based upon evidence from detailed case studies, and the different types of networks between these players that influence their decision making. Key to the model is that these networks are dynamic and co-evolving, something that has rarely been considered in social network analysis. The results presented here demonstrate how this type of simulation can aid better understanding of this complex interplay of issues. In turn, we hope that this will prove to be a powerful tool for policy development.
Journal of Artificial Societies and Social Simulation 11 (1) 5
Kyeywords: Social Simulation, Validation, Companion Modelling, Data Generating Mechanisms, Complexity
Abstract: This paper draws on the metaphor of a spectrum of models ranging from the most theory-driven to the most evidence-driven. The issue of concern is the practice and criteria that will be appro- priate to validation of different models. In order to address this concern, two modelling approaches are investigated in some detailed – one from each end of our metaphorical spectrum. Windrum et al. (2007) (http://jasss.soc.surrey.ac.uk/10/2/8.html) claimed strong similarities between agent based social simulation and conventional social science – specifically econometric – approaches to empirical modelling and on that basis considered how econometric validation techniques might be used in empirical social simulations more broadly. An alternative is the approach of the French school of \'companion modelling\' associated with Bousquet, Barreteau, Le Page and others which engages stakeholders in the modelling and validation process. The conventional approach is con- strained by prior theory and the French school approach by evidence. In this sense they are at opposite ends of the theory-evidence spectrum. The problems for validation identified by Windrum et al. are shown to be irrelevant to companion modelling which readily incorporate complexity due to realistically descriptive specifications of individual behaviour and social interaction. The result combines the precision of formal approaches with the richness of narrative scenarios. Companion modelling is therefore found to be practicable and to achieve what is claimed for it and this alone is a key difference from conventional social science including agent based computational economics.
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]
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.
Journal of Artificial Societies and Social Simulation 11 (4) 6
Kyeywords: Norms, Normative Agent-Based Social Simulation, Role Theory, Methodological Individualism
Abstract: This paper describes a survey of normative agent-based social simulation models. These models are examined from the perspective of the foundations of social theory. Agent-based modelling contributes to the research program of methodological individualism. Norms are a central concept in the role theoretic concept of action in the tradition of Durkheim and Parsons. This paper investigates to what extend normative agent-based models are able to capture the role theoretic concept of norms. Three methodological core problems are identified: the question of norm transmission, normative transformation of agents and what kind of analysis the models contribute. It can be shown that initially the models appeared only to address some of these problems rather than all of them simultaneously. More recent developments, however, show progress in that direction. However, the degree of resolution of intra agent processes remains too low for a comprehensive understanding of normative behaviour regulation.
Journal of Artificial Societies and Social Simulation 12 (1) 11
Kyeywords: Methodology, Agent Based Social Simulation, Qualitative Analysis; Evidence; Conditions of Application
Abstract: The growing field of studies of opinion formation using physical formalisms and computer simulation based tools suffers from relative lack of connection to the 'real world' societal behaviour. Such sociophysics research should aim at explaining observations or at proposing new ones. Unfortunately, this is not always the case, as many works concentrate more on the models themselves than on the social phenomena. Moreover, the simplifications proposed in simulations often sacrifice realism on the altar of computability. There are several ways to improve the value of the research, the most important by promoting truly multidisciplinary cooperation between physicists aiming to describe social phenomena and sociologists studying the phenomena in the field. In the specific case of modelling of opinion formation there are a few technical ideas which might bring the computer models much closer to reality, and therefore to improve the predictive value of the sociophysics approach.
Journal of Artificial Societies and Social Simulation 12 (3) 4
Kyeywords: Complex Adaptive System, Agent-Based Social Simulation, Supply Network, Trust
Abstract: This paper models a supply network as a complex adaptive system (CAS), in which firms or agents interact with one another and adapt themselves. And it applies agent-based social simulation (ABSS), a research method of simulating social systems under the CAS paradigm, to observe emergent outcomes. The main purposes of this paper are to consider a social factor, trust, in modeling the agents\' behavioral decision-makings and, through the simulation studies, to examine the intermediate self-organizing processes and the resulting macro-level system behaviors. The simulations results reveal symmetrical trust levels between two trading agents, based on which the degree of trust relationship in each pair of trading agents as well as the resulting collaboration patterns in the entire supply network emerge. Also, it is shown that agents\' decision-making behavior based on the trust relationship can contribute to the reduction in the variability of inventory levels. This result can be explained by the fact that mutual trust relationship based on the past experiences of trading diminishes an agent\'s uncertainties about the trustworthiness of its trading partners and thereby tends to stabilize its inventory levels.
Matthias Meyer, Iris Lorscheid and Klaus G. Troitzsch
Journal of Artificial Societies and Social Simulation 12 (4) 12
Kyeywords: Citation Analysis, Co-Citation Analysis, Lines of Research, Multidisciplinary, Science Studies, Social Simulation
Abstract: Social simulation is often described as a multidisciplinary and fast-moving field. This can make it difficult to obtain an overview of the field both for contributing researchers and for outsiders who are interested in social simulation. The Journal for Artificial Societies and Social Simulation (JASSS) completing its tenth year provides a good opportunity to take stock of what happened over this time period. First, we use citation analysis to identify the most influential publications and to verify characteristics of social simulation such as its multidisciplinary nature. Then, we perform a co-citation analysis to visualize the intellectual structure of social simulation and its development. Overall, the analysis shows social simulation both in its early stage and during its first steps towards becoming a more differentiated discipline.
Stuart Rossiter, Jason Noble and Keith R.W. Bell
Journal of Artificial Societies and Social Simulation 13 (1) 10
Kyeywords: Social Simulation, Methodology, Epistemology, Ideology, Validation
Abstract: Because of features that appear to be inherent in many social systems, modellers face complicated and subjective choices in positioning the scientific contribution of their research. This leads to a diversity of approaches and terminology, making interdisciplinary assessment of models highly problematic. Such modellers ideally need some kind of accessible, interdisciplinary framework to better understand and assess these choices. Existing texts tend either to take a specialised metaphysical approach, or focus on more pragmatic aspects such as the simulation process or descriptive protocols for how to present such research. Without a sufficiently neutral treatment of why a particular set of methods and style of model might be chosen, these choices can become entwined with the ideological and terminological baggage of a particular discipline. This paper attempts to provide such a framework. We begin with an epistemological model, which gives a standardised view on the types of validation available to the modeller, and their impact on scientific value. This is followed by a methodological framework, presented as a taxonomy of the key dimensions over which approaches are ultimately divided. Rather than working top-down from philosophical principles, we characterise the issues as a practitioner would see them. We believe that such a characterisation can be done 'well enough', where 'well enough' represents a common frame of reference for all modellers, which nevertheless respects the essence of the debate's subtleties and can be accepted as such by a majority of 'methodologists'. We conclude by discussing the limitations of such an approach, and potential further work for such a framework to be absorbed into existing, descriptive protocols and general social simulation texts.
Pierre Livet, Jean-Pierre Muller, Denis Phan and Lena Sanders
Journal of Artificial Societies and Social Simulation 13 (1) 3
Kyeywords: Ontology, Agent-Based Computational Economic, Agent-Based Model of Simulation, Model Design, Model Building, Knowledge Framework, Spatial Simulation, Social Simulation, Ontological Test
Abstract: Agent-Based Models are useful to describe and understand social, economic and spatial systems\' dynamics. But, beside the facilities which this methodology offers, evaluation and comparison of simulation models are sometimes problematic. A rigorous conceptual frame needs to be developed. This is in order to ensure the coherence in the chain linking at the one extreme the scientist\'s hypotheses about the modeled phenomenon and at the other the structure of rules in the computer program. This also systematizes the model design from the thematician conceptual framework as well. The aim is to reflect upon the role that a well defined ontology, based on the crossing of the philosophical and the computer science insights, can play to solve such questions and help the model building. We analyze different conceptions of ontology, introduce the \'ontological test\' and show its usefulness to compare models. Then we focus on the model building and show the place of a systematic ABM ontology. The latter process is situated within a larger framework called the \'knowledge framework\' in which not only the ontologies but also the notions of theory, model and empirical data take place. At last the relation between emergence and ontology is discussed.
Journal of Artificial Societies and Social Simulation 13 (1) 7
Kyeywords: Agent-Based Modeling Methodology, M2M, Social Simulation, Computational Social Science, Social Complexity, Inner Asia
Abstract: Social simulation - an emerging field of computational social science - has progressed from simple toy models to increasingly realistic models of complex social systems, such as agent-based models where heterogeneous agents interact with changing natural or artificial environments. These larger, multidisciplinary projects require a scientific research methodology distinct from, say, simpler social simulations with more limited scope, intentionally minimal complexity, and typically under a single investigator. This paper proposes a methodology for complex social simulations - particularly inter- and multi-disciplinary socio-natural systems with multi-level architecture - based on a succession of models akin to but distinct from the late Imre Lakatos' notion of a 'research programme'. The proposed methodology is illustrated through examples from the Mason-Smithsonian project on agent-based models of the rise and fall of polities in Inner Asia. While the proposed methodology requires further development, so far it has proven valuable for advancing the scientific objectives of the project and avoiding some pitfalls.
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.
Journal of Artificial Societies and Social Simulation 13 (3) 8
Kyeywords: Agent-Based Social Simulation, Weak Emergence, Social Networks, Kolmogorov Complexity, Upward Causation, Downward Causation
Abstract: This paper interprets a particular agent-based social simulation (ABSS) in terms of the third way of understanding agent-based simulation proposed by Conte. It is proposed that the normalized compression distance (derived from estimates of Kolmogorov complexity) between the initial and final macrolevel states of the ABSS provides a quantitative measure of the degree to which the results obtained via the ABSS might be obtained via a closed-form expression. If the final macrolevel state of an ABSS can only be obtained by simulation, this confers on agent-based social simulations a special status. Future empirical (computational) work and epistemological analyses are proposed.
Shah Jamal Alam, Armando Geller, Ruth Meyer and Bogdan Werth
Journal of Artificial Societies and Social Simulation 13 (4) 6
Kyeywords: Cognition, Contextualized Reasoning, Evidence-Driven Agent-Based Social Simulation, Empirical Agent-Based Social Simulation, Rich Cognitive Modelling, Tzintzuntzan
Abstract: In many computational social simulation models only cursory reference to the foundations of the agent cognition used is made and computational expenses let many modellers chose simplistic agent cognition architectures. Both choices run counter to expectations framed by scholars active in the domain of rich cognitive modelling that see agent reasoning as socially inherently contextualized. The Manchester school of social simulation proposed a particular kind of a socially contextualized reasoning mechanism, so called endorsements, to implement the cognitive processes underlying agent action selection that eventually causes agent interaction. Its usefulness lies in its lightweight architecture and in taking into account folk psychological conceptions of how reasoning works. These and other advantages make endorsements an amenable tool in everyday social simulation modelling. A yet outstanding comprehensive introduction to the concept of endorsements is provided and its theoretical basis is extended and extant research is critically reviewed. Improvements to endorsements regarding memory and perception are suggested and tested against a case-study.
Wolfgang Balzer and Klaus Manhart
Journal of Artificial Societies and Social Simulation 14 (4) 11
Kyeywords: Social Simulation, Process, Science, Theory, Social Science, Philosophy of Science
Abstract: We lay open a position concerning the difference between scientific processes and processes in science. Not all processes in science are scientific. This leads into the center of social simulation. More scientific theories should be incorporated in social simulations, and this should lead to more united structural approaches.
Flaminio Squazzoni and Károly Takács
Journal of Artificial Societies and Social Simulation 14 (4) 3
Kyeywords: Peer Review, Social Simulation, Social Norms, Selection Biases, Science Policy
Abstract: This article suggests to view peer review as a social interaction problem and shows reasons for social simulators to investigate it. Although essential for science, peer review is largely understudied and current attempts to reform it are not supported by scientific evidence. We suggest that there is room for social simulation to fill this gap by spotlighting social mechanisms behind peer review at the microscope and understanding their implications for the science system. In particular, social simulation could help to understand why voluntary peer review works at all, explore the relevance of social sanctions and reputational motives to increase the commitment of agents involved, cast light on the economic cost of this institution for the science system and understand the influence of signals and social networks in determining biases in the reviewing process. Finally, social simulation could help to test policy scenarios to maximise the efficacy and efficiency of various peer review schemes under specific circumstances and for everyone involved.
Ioan Alfred Letia and Radu Razvan Slavescu
Journal of Artificial Societies and Social Simulation 15 (3) 7
Kyeywords: Agent Based Social Simulation, Trust, Reputation, Cognitive Modeling, Multi-Modal Logic
Abstract: We employ a multimodal logic in a decision making mechanism involving trust and reputation. The mechanism is then used in a community of interacting agents which develop cooperative relationships, assess the results against several quality criteria and possibly publish their beliefs inside the group. A new definition is proposed for describing how an agent deals with the common reputation information and with divergent opinions. The definition permits selecting and integrating the knowledge obtained from the peers, based on their perceived trust, as well as on threshold called critical mass. The influence of this parameter and of the number of agents supporting a sentence over its adoption are then investigated.
Flaminio Squazzoni and Niccolò Casnici
Journal of Artificial Societies and Social Simulation 16 (1) 10
Kyeywords: JASSS, Social Simulation, Bibliometric Analysis, Impact, Inter-Journal Citations
Abstract: This paper examines the bibliometric impact of JASSS on other ISI- and Scopus-indexed sources by examining inward and outward citations and their inter-relation. Given the prestige of JASSS, this analysis can measure the growth and dynamics of social simulation and give us an indication of the direction in which social simulation is moving. Results show that the impact of JASSS is higher in computer sciences, physics and ecology than it is in the social sciences, even though JASSS-indexed articles tend to be more concerned with social science-related topics. Looking at inter-journal citations revealed an interesting citation structure: JASSS collected its largest percentage of citations from non-social science-focused journals while directing more citations within its own articles toward works published in social science journals. On the one hand, this would confirm that social simulation is not yet recognised in the social science mainstream. On the other hand, this may indicate that the cross-disciplinary nature of JASSS allows it to promulgate social science theories and findings in other distant communities.
Guillaume Deffuant, Gérard Weisbuch, Frederic Amblard and Thierry Faure
Journal of Artificial Societies and Social Simulation 16 (1) 11
Kyeywords: Opinion Dynamics, Social Simulation, Agents Based Model
Abstract: Meadows and Cliff (2012) failed to replicate the results of Deffuant et al. (2002) and concluded that our paper was wrong. In this note, we show that the conclusions of Meadows and Cliff are due to a wrong computation of indicator y, which was not fully specified in our 2002 paper. In particular, Meadows and Cliff compute indicator y before model convergence whereas this indicator should be computed after model convergence.
Emmanuel Dubois, Olivier Barreteau and Véronique Souchère
Journal of Artificial Societies and Social Simulation 16 (1) 2
Kyeywords: Agent-Based Social Simulation, Role Playing Game, Companion Modelling, Attitude-Behaviour Relations, Attitude Change, Game Setting Effects
Abstract: Role playing games (RPGs) can be used as participatory simulation methods for environmental management. However, researchers in the field need to be aware of the influence of the game settings on participants' behavioural patterns and attitudes, before fine tuning the design and use of their games. We developed an agent-based model (CauxAttitude) to assess the framing induced by the conditions of implementation of a specific game, named CauxOpération, on possible changes in participants' attitudes. We designed CauxAttitude on the basis of social psychology theories that describe relations between attitudes and behaviours, as well as on observations of CauxOpération sessions. In this paper, we describe how the model behaved according to variations in the initialization of the parameters, our aim being to explore the effects of subjective choices concerning model design and implementation. The results of our simulations enabled us to identify effects of game settings we explored, including the choice of the population of participants or of the number of participants made by the game designer. Our results also revealed the underlying mechanisms that explain the effects of game settings. These provide clues to the game designer on how to manage them.
Amineh Ghorbani, Pieter Bots, Virginia Dignum and Gerard Dijkema
Journal of Artificial Societies and Social Simulation 16 (2) 9
Kyeywords: Modelling Language, Model-Driven Engineering, Institutions, Social Simulation, Meta-Model
Abstract: In this paper we introduce and motivate a conceptualization framework for agent-based social simulation, MAIA: Modelling Agent systems based on Institutional Analysis. The MAIA framework is based on Ostrom's Institutional Analysis and Development framework, and provides an extensive set of modelling concepts that is rich enough to capture a large range of complex social phenomena. Developing advanced agent-based models requires substantial experience and knowledge of software development knowledge and skills. MAIA has been developed to help modellers who are unfamiliar with software development to conceptualize and implement agent-based models. It provides the foundation for a conceptualization procedure that guides modellers to adequately capture, analyse, and understand the domain of application, and helps them report explicitly on the motivations behind modelling choices. A web-based application supports conceptualization with MAIA, and outputs an XML file which is used to generate Java code for an executable simulation.
Journal of Artificial Societies and Social Simulation 16 (3) 11
Kyeywords: Social Simulation, Agent-Based Models (ABM), Theorem-Proof Approach, Mate-Search Problem, Two-Sided Matching, Job Matching
Abstract: This paper discusses an extended version of the matching problem which includes the mate search problem; this version is a generalization of a traditional optimization problem. The matching problem is extended to a form of the asymmetric two-sided matching problem. An agent-based simulation model is built and simulation results are presented. Todd and Miller (1999) simulated the two-sided matching problem in a symmetric setting. In his model, there are the same number of agents in both parties (groups), each of whom has his/her own mate value. Each agent in a party tries to find his/her mate in the other party, based on his/her candidate's mate value and his/her own aspiration level for his/her partner's mate value. Each agent learns his/her own mate value and adjusts his/her aspiration level through the trial period (adolescence). Todd and Miller (1999) tried several search rules and learning mechanisms that are symmetric for both parties. In the present paper, Todd and Miller's (1999) model is extended to an asymmetric setting where the two parties have different numbers of agents, and the search rule and the learning mechanism for the two parties differ. Through the simulation, the search rules and the learning mechanisms which were identified to be appropriate in a symmetric setting are revealed to be inappropriate in the asymmetric setting and the reason why this is so is discussed. Furthermore, some general facts are derived using a mathematical theorem-proof approach. Some of these facts are used to direct a revision of the model, and a revised simulation model is presented. An implication is obtained for practical situations in asymmetric matching setting. For example, in the job hunting case, if job applicants want to finish their job hunting successfully, they should be modest at the beginning of the hunt.
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.
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.
Sukaina Bharwani, Mònica Coll Besa, Richard Taylor, Michael Fischer, Tahia Devisscher and Chrislain Kenfack
Journal of Artificial Societies and Social Simulation 18 (1) 3
Kyeywords: Knowledge Elicitation, Decision-Making, Climate Adaptation, Verification and Validation, Social Simulation, Tacit Knowledge
Abstract: This paper describes a participatory and collaborative process for formalising qualitative data, using research from southeast Cameroon, how these results can provide input to an social simulation model, and what insights they can provide in better understanding decision-making in the region. Knowledge Elicitation Tools (KnETs) have been used to support a body of existing research on local strategies that build community adaptive capacity and support sustainable forest management under a range of socio-environmental and climatic stressors. The output of this approach is a set of decision rules which complements previous analysis of differentiated vulnerability of forest communities. Improvements to the KnETs methodology, such as new statistical measurements, make it easier to generate inputs for a social simulation model, such as agent attributes and heterogeneity, as well as informing which scenarios to prioritise during model development and testing. The KnETs process served as a vehicle to structure a large volume of empirical data, to identify the most salient drivers of decision-making amongst different actors, to uncover tacit knowledge and to make recommendations about which strategic interventions should be further explored in a social simulation and by local organizations planning interventions. It was notable that there were many common rule drivers for men and women from the same households, though they participated in the game-interviews separately. At the same time, though strategies were common to both poor and better-off farmers, differences lay in the package of strategies chosen – the number and type of strategies as well the drivers factors – and how they were prioritised with respect to each farmer’s goal.
Mason Wright and Pratim Sengupta
Journal of Artificial Societies and Social Simulation 18 (2) 3
Kyeywords: Multi-Agent Models, Lobbying, Public Choice, Bounded Rationality, Voting Behavior, Social Simulation
Abstract: In this paper, we investigate the interactions among oligarchs, political parties, and voters using an agent-based modeling approach. We introduce the OLIGO model, which is based on the spatial model of democracy, where voters have positions in a policy space and vote for the party that appears closest to them, and parties move in policy space to seek more votes. We extend the existing literature on agent-based models of political economy in the following manner: (1) by introducing a new class of agents – oligarchs – that represent leaders of firms in a common industry who lobby for beneficial subsidies through campaign donations; and (2) by investigating the effects of ideological preferences of the oligarchs on legislative action. We test hypotheses from the literature in political economics on the behavior of oligarchs and political parties as they interact, under conditions of imperfect information and bounded rationality. Our key results indicate that (1) oligarchs tend to donate less to political campaigns when the parties are more resistant to changing their policies, or when voters are more in-formed; and (2) if Oligarchs donate to parties based on a combination of ideological and profit motivations, Oligarchs will tend to donate at a lower equilibrium level, due to the influence of lost profits. We validate these outcomes via comparisons to real world polling data on changes in party support over time.
Jonathan Ozik, Nicholson Collier, Todd Combs, Charles M. Macal and Michael North
Journal of Artificial Societies and Social Simulation 18 (3) 11
Kyeywords: Agent-Based Modeling, Statecharts, Agent-Based Social Simulation, Repast Simphony, Software Engineering Processes
Abstract: Agent states and transitions between states are important abstractions in agent-based social simulation (ABSS). Although it is common to develop ad hoc implementations of state-based and transition-based agent behaviors, “best practice” software engineering processes provide transparent and formally grounded design notations that translate directly into working implementations. Statecharts are a software engineering design methodology and an explicit visual and logical representation of the states of system components and the transitions between those states. Used in ABSS, they can clarify a model’s logic and allow for efficient software engineering of complex state-based models. In addition to agent state and behavioral logic representation, visual statecharts can also be useful for monitoring agent status during a simulation, quickly conveying the underlying dynamics of complex models as a simulation evolves over time. Visual approaches include drag-and-drop editing capabilities for constructing state-based models of agent behaviors and conditions for agent state transitions. Repast Simphony is a widely used, open source, and freely accessible agent-based modeling toolkit. While it is possible for Repast Simphony users to create their own implementations of state-based agent behaviors and even create dynamic agent state visualizations, the effort involved in doing so is usually prohibitive. The new statecharts framework in Repast Simphony, a subset of Harel’s statecharts, introduces software engineering practices through the use of statecharts that directly translate visual representations of agent states and behaviors into software implementations. By integrating an agent statecharts framework into Repast Simphony, we have made it easier for users at all levels to take advantage of this important modeling paradigm. Through the visual programming that statecharts afford, users can effectively create the software underlying agents and agent-based models. This paper describes the development and use of the free and open source Repast Simphony statecharts capability for developing ABSS models.
Peer-Olaf Siebers and Paul Davidsson
Journal of Artificial Societies and Social Simulation 18 (3) 13
Kyeywords: Agent-Based Social Simulation, Software Engineering, Software Architectures, UML
Abstract: This special section on "Engineering Agent-Based Social Simulations" aims to represent the current state of the art in using Software Engineering (SE) methods in ABSS. It includes a mixture of theoretically oriented papers that describe frameworks, notations and methods adapted from SE and practice-oriented papers that demonstrate the application of SE methods in real world ABSS projects.
Sabrina Scherer, Maria Wimmer, Ulf Lotzmann, Scott Moss and Daniele Pinotti
Journal of Artificial Societies and Social Simulation 18 (3) 14
Kyeywords: Model-Driven Development, Agent-Based Policy Models, Annotation of Policy Models, Conceptual Models, Social Simulation Models, Provenance Information
Abstract: Agent-based policy modelling is an application of agent-based social simulation. In this contribution it is applied to strategic policy making in the public sector. Open government principles relevant in this domain demand solutions that trace the origins of modelling decisions from narrative texts (background documents and stakeholder scenarios) through the whole policy modelling process up to the simulation results. With the help of such traces, decisions made on the basis of such simulation results are more transparent and comprehensible. This paper presents a conceptual model-driven approach developed and implemented in the OCOPOMO project. The approach ensures traceability by integrating technologies for agent-based social simulation, semantic web and model-driven development. Narrative texts are transferred into Consistent Conceptual Description (CCD) models. Those CCD models are transferred semi-automatically into formal policy models implemented in the DRAMS (Declarative Rule-based Agent Modelling System) language. These formal policy models are further elaborated (i.e. the policy modeller has still full flexibility in programming the model), and runnable simulation models are programmed. From the simulation logs, model-based scenarios are generated to interpret and support a better understanding of simulation results. The model-based scenarios are textual narratives with charts summarising the output produced by the simulation runs. Thereby passages in these texts are linked with documents containing original narrative scenarios. These traces are realised via the CCD models. A well-elaborated policy modelling process and a software toolbox support the approach. A pilot case exemplifies the application of the process and the toolbox. Evaluation results from the OCOPOMO project show benefits as well as limitations of the approach. We also reflect how the process and toolbox can be transferred into other application domains.
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.
L. Andrew Bollinger, Martti J. van Blijswijk, Gerard P.J. Dijkema and Igor Nikolic
Journal of Artificial Societies and Social Simulation 19 (1) 1
Kyeywords: Socio-Technical Systems, Electricity Systems, Modelling Tools, Social Simulation, Netlogo, Matpower
Abstract: The growing importance of links between the social and technical dimensions of the electricity infrastructure mean that many research problems cannot be effectively addressed without joint consideration of social and technical dynamics. This paper motivates the need for and introduces a tool to facilitate the development of linked social and technical models of electric power systems. The tool, called MatpowerConnect, enables the runtime linkage of Netlogo - an oft-used modelling platform in the social simulation domain - with Matpower - a common power flow simulation package in the power systems domain. MatpowerConnect opens up new modelling possibilities for social simulation researchers active in the study of electricity systems. It offers ease of use coupled with a high degree of realism with which electricity infrastructure functionality is captured. We describe the development and use of two demonstration models using MatpowerConnect. These models illustrate two types of problems and system scales that can be addressed. In the first model we explore the consequences of actors' adaptive strategies on the performance of a small-scale power system. In the second model we simulate the effects of different regulatory regimes on network investment in a supra-national electricity transmission system to explore the long-term consequences for network development and social welfare. In both cases, the extension enables capturing a critical functionality of electric power systems, while allowing model development efforts to focus on social simulation aspects. Resources for using the extension are provided in conjunction with this paper.
Thomas Farrenkopf, Michael Guckert, Neil Urquhart and Simon Wells
Journal of Artificial Societies and Social Simulation 19 (4) 14
Kyeywords: Social Simulation, Ontology, BDI Agent
Abstract: Within business games there is a need to provide realistic feedback for decisions made, if such business games are to continue to remain relevant in increasingly complex business environments. We address this problem by using software agents to simulate individuals and to model their actions in response to business decisions. In our initial studies we have used software agents to simulate consumers who make buying decisions based on their private preferences and those prevalent within their social network. This approach can be applied to search for behavioural patterns in social structures and to verify predicted values based on a priori theoretical considerations. Individual behaviour can be modelled for each agent and its effects within the marketplace can be examined by running simulations. Our simulations are founded upon the BDI software model (belief-desire-intention) combined with ontologies to make world knowledge available to the agents which can then determine their actions in accordance with this knowledge. We demonstrate how ontologies can be integrated into the BDI concept utilising the Jadex agent framework. Our examples are based upon the simulation of market mechanisms within the context of different industries. We use a framework, developed previously, known as AGADE within which each agent evolves its knowledge using an ontology maintained during the simulation. This generic approach allows the simulation of various consumer scenarios which can be modelled by creating appropriate ontologies.
Kei-Leo Brousmiche, Jean-Daniel Kant, Nicolas Sabouret and François Prenot-Guinard
Journal of Artificial Societies and Social Simulation 19 (4) 2
Kyeywords: Social Simulation, Attitude Formation, Cognitive Modeling, Calibration Using Field Data
Abstract: Attitude is a key concept in social psychology. The paper presents a novel agent-based model to simulate attitude formation by combining a rational and an emotional components based on cognitive, psychological and social theories. Individuals of the artificial population perceive actions taken by actors such as government or brands, they form an attitude toward them and also communicate the events through a social network. The model outputs are first studied through a functional analysis in which some unique macroscopic behaviors have emerged such as the impact of social groups, the resistance of the population toward disinformation campaigns or the social pressure. We then applied our model on a real world scenario depicting the effort of French Forces in their stabilization operations in Kapisa (Afghanistan) between 2010 and 2012. We calibrated the model parameters based on this scenario and the results of opinion polls that were conducted in the area during the same period about the sentiment of the population toward the Forces. Our model was able to reproduce polls results with a global error under 3%. Based on these results, we show the different dynamics tendencies that emerged among the population by applying a non-supervised classification algorithm.
Jonas Hauke, Iris Lorscheid and Matthias Meyer
Journal of Artificial Societies and Social Simulation 20 (1) 5
Kyeywords: Social Simulation, Lines of Research, Multidisciplinary, Citation Analysis, Co-Citation Analysis
Abstract: The research field of social simulation comprises many topics and research directions. A previous study about the early years indicated that the community has evolved into a differentiated discipline. This paper investigates the recent development of social simulation as reflected in Journal of Artificial Societies and Social Simulation (JASSS) publications from 2008 to 2014. By using citation analysis, we identify the most influential publications and study the characteristics of citations. Additionally, we analyze the development of the field with respect to research topics and their structure in a co-citation analysis. The citation characteristics support the continuing highly multidisciplinary character of JASSS. Prominently cited are methodological papers and books, standards, and NetLogo as the main simulation tool. With respect to the focus of this research, we observe continuity in topics such as opinion dynamics and the evolution of cooperation. While some topics disappeared such as learning, new subjects emerged such as marriage formation models and tools and platforms. Overall, one can observe a maturing inter- and multidisciplinary scientific community in which both methodological issues and specific social science topics are discussed and standards have emerged.
Carole Adam and Benoit Gaudou
Journal of Artificial Societies and Social Simulation 20 (3) 12
Kyeywords: Human Behaviour Modelling, Agent-Based Social Simulation, Crisis Management
Abstract: This paper describes a model for raising the decision-makers' awareness of the real (irrational and subjective) behaviours of the population in crisis situations. We analyse residents' statements and police hearings gathered after Victoria Black Saturday bushfires in 2009 to deduce a model of human behaviour based on the distinction between objective (capabilities, danger) and subjective (confidence, risk aversion) attributes, and on individual motivations. We evaluate it against observed behaviour archetypes and statistics, and show its explicative value.
Pierpaolo Angelini, Giovanni Cerulli, Federico Cecconi, Maria-Augusta Miceli and Bianca Potì
Journal of Artificial Societies and Social Simulation 20 (4) 4
Kyeywords: R&D Policy, Networks, Complexity, Social Simulation
Abstract: This paper presents an agent-based micro-policy simulation model assessing public R&D policy effect when R&D and non-R&D performing companies are located within a network. We set out by illustrating the behavioural structure and the computational logic of the proposed model; then, we provide a simulation experiment where the pattern of the total level of R&D activated by a fixed amount of public support is analysed as function of companies’ network topology. More specifically, the suggested simulation experiment shows that a larger “hubness” of the network is more likely accompanied with a decreasing median of the aggregated total R&D performance of the system. Since the aggregated firm idiosyncratic R&D (i.e., the part of total R&D independent of spillovers) is slightly increasing, we conclude that positive cross-firm spillover effects - in the presence of a given amount of support - have a sizeable impact within less centralized networks, where fewer hubs emerge. This may question the common wisdom suggesting that larger R&D externality effects should be more likely to arise when few central champions receive a support.
Davide Secchi and Stephen J. Cowley
Journal of Artificial Societies and Social Simulation 21 (1) 13
Kyeywords: Organizational Cognition, Distributed Cognition, E-Cognition, Impact Factor, Perceived Scientific Value, Social Organizing, Agent-Based Simulation Modeling
Abstract: This article offers an alternative perspective on organizational cognition based on e-cognition whereby appeal to systemic cognition replaces the traditional computational model of the mind that is still extremely popular in organizational research. It uses information processing, not to explore inner processes, but as the basis for pursuing organizational matters. To develop a theory of organizational cognition, the current work presents an agent-based simulation model based on the case of how individual perception of scientific value is affected by and affects organizational intelligence units' (e.g., research groups', departmental) framing of the notorious impact factor. Results show that organizational cognition cannot be described without an intermediate meso scale – called here social organizing – that both filters and enables the many kinds of socially enabled perception, action and behavior that are so characteristic of human cognition.
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.
Mathieu Bourgais, Patrick Taillandier, Laurent Vercouter and Carole Adam
Journal of Artificial Societies and Social Simulation 21 (2) 5
Kyeywords: Emotion, Social Simulation, Survey
Abstract: Emotions play a key role in human behavior. Being able to integrate them in models is thus a major issue to improve the believability of agent-based social simulations. However, even though these last years have seen the emergence of many emotional models usable for simulations, many modelers still tend to use simple ad hoc emotional models. To support this view, this article proposes a survey of the different practices of modelers in terms of implementations of emotional models. We then present different emotional architectures that already exist and that can be used by modelers. The main goal is to understand the way emotions are used today in social simulations, in order for the community to unify its uses of emotional agents.
Ahmed Laatabi, Nicolas Marilleau, Tri Nguyen-Huu, Hassan Hbid and Mohamed Ait Babram
Journal of Artificial Societies and Social Simulation 21 (2) 9
Kyeywords: Empirical Agent-Based Models, ODD Protocol, ODD+2D, Mapping, Data Analysis, Social Simulation
Abstract: The quantity of data and processes used in modeling projects has been dramatically increasing in recent years due to the progress in computation capability and to the popularity of new approaches such as open data. Modelers face an increasing difficulty in analyzing and modeling complex systems that consist of many heterogeneous entities. Adapting existing models is relevant to avoid dealing with the complexity of writing and studying a new model from scratch. ODD (Overview, Design concepts, Details) protocol has emerged as a solution to document Agent-Based Models (ABMs). It appears to be a convenient solution to address significant problems such as comprehension, replication, and dissemination. However, it lacks a standard that formalizes the use of data in empirical models. This paper tackles this issue by proposing a set of rules that outline the use of empirical data inside an ABM. We call this new protocol ODD+2D (ODD+Decision + Data). ODD+2D integrates a mapping diagram called DAMap (Data to Agent Mapping). This mapping model formalizes how data are processed and mapped to agent-based models. In this paper, we focus on the architecture of ODD+2D, and we illustrate it with a residential mobility model in Marrakesh.
Segismundo S. Izquierdo and Luis R. Izquierdo
Journal of Artificial Societies and Social Simulation 21 (3) 2
Kyeywords: Social Simulation, Decision Support Systems, Deductive Inference, Fuzzy Logic, Mamdani
Abstract: Fuzzy logic presents many potential applications for modelling and simulation. In particular, this paper analyses one of the most popular fuzzy logic techniques: Mamdani systems. Mamdani systems can look particularly appealing because they are designed to incorporate expert knowledge in the form of IF-THEN rules expressed in natural language. While this is an attractive feature for modelling and simulating social and other complex systems, its actual application presents important caveats. This paper studies the potential use of Mamdani systems to explore the logical consequences of a model based on IF-THEN rules via simulation. We show that in the best-case scenario a Mamdani system provides a function that complies with its generating set of IF-THEN rules, which is a different exercise from that of finding the relation or consequences implied by those rules. In general, the logical consequences of a set of rules cannot be captured by a single function. Furthermore, the consequences of an IF-THEN rule in a Mamdani system can be very different from the consequences of that same rule in a system governed by the most basic principles of logical deductive inference. Thus, care must be taken when applying this tool to study “the consequences” of a set of hypothesis. Previous analyses have typically focused on particular steps of the Mamdani process, while here we present a holistic assessment of this technique for (deductive) simulation purposes.
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.
Alireza Mansouri and Fattaneh Taghiyareh
Journal of Artificial Societies and Social Simulation 23 (2) 3
Kyeywords: Opinion Formation, Noise, Agent-Based Modeling, Social Impact Model, Phase Transition
Abstract: Human interactions and opinion exchanges lead to social opinion dynamics, which is well described by opinion formation models. In these models, a random parameter is usually considered as the system noise, indicating the individual's inexplicable opinion changes. This noise could be an indicator of any other influential factors, such as public media, affects, and emotions. We study phase transitions, changes from one social phase to another, for various noise levels in a discrete opinion formation model based on the social impact theory with a scale-free random network as its interaction network topology. We also generate another similar model using the concept of social power based on the agents' node degrees in the interaction network as an estimation for their persuasiveness and supportiveness strengths and compare both models from phase transition viewpoint. We show by agent-based simulation and analytical considerations how opinion phases, including majority and non-majority, are formed in terms of the initial population of agents in opinion groups and noise levels. Two factors affect the system phase in equilibrium when the noise level increases: breaking up more segregated groups and dominance of stochastic behavior of the agents on their deterministic behavior. In the high enough noise levels, the system reaches a non-majority phase in equilibrium, regardless of the initial combination of opinion groups. In relatively low noise levels, the original model and the model whose agents' strengths are proportional to their centrality have different behaviors. The presence of a few high-connected influential leaders in the latter model consequences a different behavior in reaching equilibrium phase and different thresholds of noise levels for phase transitions.
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.
Mathieu Bourgais, Patrick Taillandier and Laurent Vercouter
Journal of Artificial Societies and Social Simulation 23 (4) 12
Kyeywords: Social Simulation, Agent Architecture, BDI, Emotions, Personality, Emotional Contagion
Abstract: Over the last few years, the use of agent-based simulations to study social systems has spread to many domains (e.g., geography, ecology, sociology, economy). These simulations aim to reproduce real life situations involving human beings and thus need to integrate complex agents to match the behavior of the simulated people. Therefore, notions such as cognition, emotions, personality, social relationships or norms have to be taken into account, but there is currently no agent architecture that could incorporate all these features and be used by the majority of modelers, including those with low levels of skills in programming. In this paper, the BEN (Behavior with Emotions and Norms) architecture is introduced to tackle this issue. It is a modular architecture based on the BDI model of cognition and featuring modules to add emotions, emotional contagion, personality, social relationships and norms to agent behavior. This architecture is integrated into the GAMA simulation platform. An application of BEN to the simulation of the evacuation of a nightclub on fire is presented and shows the complexity of behaviors that may be developed with this architecture to create credible and expressive simulations.
Tae-Sub Yun and Il-Chul Moon
Journal of Artificial Societies and Social Simulation 23 (4) 5
Kyeywords: Housing Market, Macro-Prudential Policy, Loan-To-Value, Debt-To-Income, Agent-Based Modeling, Policy Impact Analysis
Abstract: This paper introduces an agent-based model of a housing market with macro-prudential policy experiments. Specifically, the simulation model is used to examine the effects of a policy setting on loan-to-value (LTV) and debt-to-income (DTI), which are policy instruments several governments use to regulate the housing market. The simulation model illustrates the interactions among the households, the house suppliers, and the real estate brokers. We model each household in the population as either seller or buyer, and some of households may behave as speculators in the housing market. To better understand the impact of the policies, we used the real-world observations from the Korean housing market, which include various economic conditions, policy variables, and Korean census data. Our baseline model is quantitatively validated to the price index and the transaction volume of the past Korean housing market. After validation, we show the empirical effectiveness of setting LTV and DTI towards house prices, transaction volumes, and the amount of households' mortgages. Furthermore, we investigate the simulation results for the owner-occupier rate of households. These investigations provide the policy analyses in Korea's housing market, and other governments with LTV and DTI regulations.
Lucas Sage and Andreas Flache
Journal of Artificial Societies and Social Simulation 24 (2) 2
Kyeywords: Agent-Based Model, Social Simulation, Segregation, School-Segregation, School-Choice, Discrete-Choice-Model
Abstract: Schelling and Sakoda prominently proposed computational models suggesting that strong ethnic residential segregation can be the unintended outcome of a self-reinforcing dynamic driven by choices of individuals with rather tolerant ethnic preferences. There are only few attempts to apply this view to school choice, another important arena in which ethnic segregation occurs. In the current paper, we explore with an agent-based theoretical model similar to those proposed for residential segregation, how ethnic tolerance among parents can affect the level of school segregation. More specifically, we ask whether and under which conditions school segregation could be reduced if more parents hold tolerant ethnic preferences. We move beyond earlier models of school segregation in three ways. First, we model individual school choices using a random utility discrete choice approach. Second, we vary the pattern of ethnic segregation in the residential context of school choices systematically, comparing residential maps in which segregation is unrelated to parents’ level of tolerance to residential maps reflecting their ethnic preferences. Third, we introduce heterogeneity in tolerance levels among parents belonging to the same group. Our simulation experiments suggest that ethnic school segregation can be a very robust phenomenon, occurring even when about half of the population prefers segregated to mixed schools. However, we also identify a “sweet spot” in the parameter space in which a larger proportion of tolerant parents makes the biggest difference. This is the case when parents have moderate preferences for nearby schools and there is only little residential segregation. Further experimentation unraveled the underlying mechanisms.
Samuel Assefa, Aad Kessler and Luuk Fleskens
Journal of Artificial Societies and Social Simulation 24 (4) 8
Kyeywords: Social Simulation, Farmers, Soil and Water Conservation, Scenario Analysis, Ethiopia
Abstract: The sustainability of the ongoing Campaign-Based Watershed Management (CBWM) program in Ethiopia is questionable due to poor planning and implementation of the Soil and Water Conservation (SWC) structures. This study uses an empirically based, agent-based model to explore the effect of six scenarios on both area of land covered by, as well as the quality of SWC structures in three Kebeles (villages) of Boset District. The analysis revealed that integrating multiple interventions enhanced SWC most in all Kebeles. Furthermore, increasing the commitment of local government through capacity building generated most effect and yet required the lowest investment. Motivating farmers, introducing alternative livelihood opportunities and establishing and strengthening micro-watershed associations had limited, but differential influence on the outcomes across the Kebeles. However, all alternative scenarios had some added value compared to doing business as usual. Hence, in order to enhance the outcomes and sustainability of the ongoing CBWM program in the study area and other similar localities, it is crucial to pay much more attention to increasing the commitment of local government actors through capacity building. This empowers local government actors to (1) plan and more efficiently implement the program in consultation with other local actors, and (2) integrate locally sensitive need-based adaptation of the program.
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.