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70 articles matched your search for the keywords:
Agent Based Model, Resources, Norms, Hawk-Dove-Bourgeois Game

Individual Versus Social Survival Strategies

Federico Cecconi and Domenico Parisi
Journal of Artificial Societies and Social Simulation 1 (2) 1

Kyeywords: Artificial Life, Social Survival Strategies, Centralized Resources
Abstract: The paper introduces the concepts of individual survival strategies (ISS) and social survival strategies (SSS) and presents three sets of simulations of a particular type of SSS: the Central Store (CS) strategy, according to which the individuals in a group contribute part of their resources to a central mechanism that can redistribute these resources or make other uses of them. CS and ISS both allow a group of individuals to survive in a favourable environment although group size is slower to reach a steady state in the CS group because of the lower selective pressure on individuals' resource production. However, only CS groups survive in a less favourable environment apparently because the CS functions as a safety net for the individuals in the group. Although CS strategies can have this and other advantages over ISS, if individuals are left free to decide whether or not to give their resources to the CS, they tend not to do so. In other words, they abandon the CS strategy and revert to ISS. Because CS strategies characterize an increasing number of human societies since Neolithic times an important research problem is to identify and reproduce in the simulations, how groups of individuals that tend to act egoistically and not to give their resources to the CS, can be induced to do so.

Simulation Tools for Social Scientists: Building Agent Based Models with SWARM

Pietro Terna
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.

Normative Reputation and the Costs of Compliance

Cristiano Castelfranchi, Rosaria Conte and Mario Paolucci
Journal of Artificial Societies and Social Simulation 1 (3) 3

Kyeywords: Norms, Reputation, Compliance
Abstract: In this paper, the role of normative reputation in reducing the costs of complying with norms will be explored. In previous simulations (Conte & Castelfranchi 1995), in contrast to a traditional view of norms as means for increasing co-ordination among agents, the effects of normative and non-normative strategies in the control of aggression among agents in a common environment was confronted. Normative strategies were found to reduce aggression to a much greater extent than non-normative strategies, and also to afford the highest average strength and the lowest polarisation of strength among the agents. The present study explores the effects of the interaction between populations following different criteria for aggression control. In such a situation the normative agents alone bear the cost of norms, due to their less aggressive behaviour, while other agents benefit from their presence. Equity is then restored by raising the cost of aggression through the introduction of agents' reputation. This allows normative agents to avoid respecting the cheaters' private property, and to impose a price for transgression. The relevance of knowledge communication is then emphasised by allowing neighbour normative agents to communicate. In particular, the spreading of agents' reputation via communication allows normative agents to co-operate without deliberation at the expense of non-normative agents, thereby redistributing the costs of normative strategies.

Simulating Norms, Social Inequality, and Functional Change in Artificial Societies

Nicole J. Saam and Andreas G. Harrer
Journal of Artificial Societies and Social Simulation 2 (1) 2

Kyeywords: Simulation of Norms, Social Inequality, Functions of Norms
Abstract: In this paper, we compare the computational and sociological study of norms, and resimulate previous simulations (Conte and Castelfranchi 1995a, Castelfranchi, Conte and Paolucci 1998) under slightly different conditions. First, we analyze the relation between norms, social inequality and functional change more closely. Due to our results, the hypothesis stating that the "finder-keeper" norm while controlling aggression efficaciously reduces social inequality holds only in quite egalitarian societies. Throughout a variety of inegalitarian societies, it instead increases social inequality. This argument which can be traced back to Marx is being investigated by use of computer simulations of artificial societies. Second, we remodel normative behaviour from a sociological point of view by implementing Haferkamp's theory of action approach to deviant behaviour. Following the game theoretic models, the computational study of norms has up to now ignored the importance of power in explaining how norms affect social behaviour, how norms emerge, become established and internalized, and change. By simulating Haferkamp and repeating the Conte and Castelfranchi experiments, we demonstrate that it is possible to integrate power into computational models of norms.

Simulating Common Pool Resource Management Experiments with Adaptive Agents Employing Alternate Communication Routines

Peter Deadman, Edella Schlager and Randy Gimblett
Journal of Artificial Societies and Social Simulation 3 (2) 2

Kyeywords: Common Pool Resources, Intelligent Agents, Simulation, Bounded Rationality, Communication
Abstract: This paper describes the development of a series of intelligent agent simulations based on data from previously documented common pool resource (CPR) experiments. These simulations are employed to examine the effects of different institutional configurations and individual behavioral characteristics on group level performance in a commons dilemma. Intelligent agents were created to represent the actions of individuals in a CPR experiment. The agents possess a collection of heuristics and utilize a form of adaptation by credit assignment in which they select the heuristic that appears to yield the highest return under the current circumstances. These simulations allow the analyst to specify the precise initial configuration of an institution and an individual's behavioral characteristics, so as to observe the interaction of the two and the group level outcomes that emerge as a result. Simulations explore settings in which there is no communication between agents, as well as the relative effects on overall group behavior of two different communication routines. The behavior of these simulations is compared with documented CPR experiments. Future directions in the development of the technology are outlined for natural resource management modeling applications.

Using AgentSheets to Teach Simulation to Undergraduate Students

Joaquim Carvalho
Journal of Artificial Societies and Social Simulation 3 (3) forum/2

Kyeywords: Simulation, Teaching, User Interfaces to Agent Based Models
Abstract: The AgentSheets simulation software has been used for the last two years in a course for undergraduate students. The ease of use and extreme care put into the interface makes this tool a classroom success, allowing students to have hands-on experience of model construction without the overhead of learning complicated frameworks or programming languages. The limitations of the tool, in particular those that make difficult the construction of more complex models, are reviewed.

Introducing Emotions into the Computational Study of Social Norms: a First Evaluation

Alexander Staller and Paolo Petta
Journal of Artificial Societies and Social Simulation 4 (1) 2

Kyeywords: Social Norms, Appraisal Theory of Emotions ,Process Model of Emotions, Layered Agent Architecture, Simulation, JAM (BDI Agent Architecture), Micro-Macro Link, Aggression Control Case Study, Deontic Reasoning and Human Behaviour Models
Abstract: It is now generally recognised that emotions play an important functional role within both individuals and societies, thereby forming an important bond between these two levels of analysis. In particular, there is a bi-directional interrelationship between social norms and emotions, with emotions playing an instrumental role for the sustenance of social norms and social norms being an essential element of regulation in the individual emotional system. This paper lays the foundations for a computational study of this interrelationship, drawing upon the functional appraisal theory of emotions. We describe a first implementation of a situated agent architecture, TABASCOJAM, that incorporates a simple appraisal mechanism and report on its evaluation in a well-known scenario for the study of aggression control as a function of a norm, that was suitably extended. The simulation results reported in the original aggression control study were successfully reproduced, and consistent performances were achieved for extended scenarios with conditional norm obeyance. In conclusion, it is argued that the present effort indicates a promising lane towards the necessary abandonment of logical models for the explanation and simulation of human social behaviour.

Modelling the Emergence of Resource-Sharing Conventions: an Agent-Based Approach

Olivier Thebaud and Bruno Locatelli
Journal of Artificial Societies and Social Simulation 4 (2) 3

Kyeywords: Conventions, Natural Resources, Multi-Agent Systems
Abstract: This paper presents an agent-based simulation framework for the analysis of the emergence of resource-sharing conventions. The model is based on Sugden's article entitled "Spontaneous order", which looks at the conditions under which conventions regarding access to a natural resource become established. The aim of the model is to explore the potential of agent-based modelling for the analysis of these questions. First, the structure of a simulation model based on the example of driftwood collection used by Sugden is presented. Second, simulations of various scenarios about the behavioural rules followed by agents are described, and simulation results are presented. The paper concludes with a brief discussion of the advantages of agent-based models for analysing social processes such as the emergence of conventions regulating access to natural resources.

From Social Monitoring to Normative Influence

Rosaria Conte and Frank Dignum
Journal of Artificial Societies and Social Simulation 4 (2) 7

Kyeywords: Norms, Multi Agent Systems, Imitation, Social Control, Social Cognition
Abstract: This paper is intended to analyse the concepts involved in the phenomena of social monitoring and norm-based social influence for systems of normative agents. These are here defined as deliberative agents, representing norms and deciding upon them. Normative agents can use the norms to evaluate others' behaviours and, possibly, convince them to comply with norms. Normative agents contribute to the social dynamics of norms, and more specifically, of norm-based social control and influence. In fact, normative intelligence allows agents to Check the efficacy of the norms (the extent to which a norm is applied in the system in which it is in force), and possibly Urge their fellows to obey the norms. The following issues are addressed: What is norm-based control? Why and how do agents exercise control on one another? What role does it play in the spread of norms?

Group Reputation Supports Beneficent Norms

David Hales
Journal of Artificial Societies and Social Simulation 5 (4) 4

Kyeywords: Norms, Reputation, Social Groups, Group Reputation, Stereotypes
Abstract: This paper demonstrates the role of group normative reputation in the promotion of an aggression reducing possession norm in an artificial society. A previous model of normative reputation is extended such that agents are given the cognitive capacity to categorise other agents as members of a group. In the previous model reputational information was communicated between agents concerning individuals. In the model presented here reputations are projected onto whole groups of agents (a form of "stereotyping"). By stereotyping, norm followers outperform cheaters (who do not follow the norm) under certain conditions. Stereotyping, by increasing the domain of applicability of a piece of reputational information, allows agents to make informed decisions concerning interactions with agents which no other agent has previously met. However, if conditions are not conducive, stereotyping can completely negate norm following behaviour. Group reputation can be a powerful mechanism, therefore, for the promotion of beneficent norms under the right conditions.

Using Self-Designed Role-Playing Games and a Multi-Agent System to Empower a Local Decision-Making Process for Land Use Management: the SelfCormas Experiment in Senegal

Patrick D'aquino, Christophe Le Page, François Bousquet and Alassane Bah
Journal of Artificial Societies and Social Simulation 6 (3) 5

Kyeywords: Local Planning; Participatory; Land Use; Resources Management; Role Playing Games;Agent Based Modeling
Abstract: As agricultural and environmental issues are more and more inter-linked, the increasing multiplicity of stakeholders, with differing and often conflicting land use representations and strategies, underlines the need for innovative methods and tools to support their coordination, mediation and negotiation processes aiming at an improved, more decentralized and integrated natural resources management. But how can technology fit best with such a novel means of support? Even the present participatory modeling method is not really designed to avoid this technocratic drift and encourage the empowerment of stakeholders in the land use planning process. In fact, to truly integrate people and principals in the decision-making process of land use management and planning, information technology should not only support a mere access to information but also help people to participate fully in its design, process and usage. That means allow people to use the modeling support not to provide solutions, but to help people to steer their course within an incremental, iterative, and shared decision-making process. To this end, since 1997 we have experimented at an operational level (2500 km_) in the Senegal River valley a Self-Design Method that places modeling tools at stakeholders? and principals' disposal, right from the initial stages. The experiment presented here links Multi-Agent Systems and Role-Playing Games within a self-design and use process. The main objective was to test direct modeling design of these tools by stakeholders, with as little prior design work by the modeler as possible. This "self-design" experiment was organized in the form of participatory workshops which has led on discussions, appraisals, and decisions about planning land use management, already applied two years after the first workshops.

Evaluation of free Java-libraries for social-scientific agent based simulation

Robert Tobias and Carole Hofmann
Journal of Artificial Societies and Social Simulation 7 (1) 6

Kyeywords: Evaluation, Simulation Framework, Agent Based Modeling, Java, Theory Based Modeling, Data Based Modeling, Social Intervention Planning
Abstract: This paper compares four freely available programming libraries for support of social scientific agent based computer simulation: RePast, Swarm, Quicksilver, and VSEit. Our aim is evaluation to determine the simulation framework that is the best suited for theory and data based modeling of social interventions, such as information campaigns. Our first step consisted in an Internet search for programming libraries and the selection of suitable candidates for detailed evaluation on the basis of 'knock out' criteria. Next, we developed a rating system and assessed the selected simulation environments on the basis of the rating criteria. The evaluation was based on official program documentation, statements by developers and users, and the experiences and impressions of the evaluators. The evaluation results showed the RePast environment to be the clear winner. In a further step, the evaluation results were weighted according to effort/time/energy saved by social scientists by using the particular ready-made programming library as compared to doing their own programming. Once again, the weighted results show RePast to win out over the other Java based programming libraries examined.

The Ghost in the Model (and Other Effects of Floating Point Arithmetic)

Gary Polhill, Luis R. Izquierdo and Nicholas M. Gotts
Journal of Artificial Societies and Social Simulation 8 (1) 5

Kyeywords: Agent Based Modelling, Floating Point Arithmetic, Interval Arithmetic, Replication
Abstract: This paper will explore the effects of errors in floating point arithmetic in two published agent-based models: the first a model of land use change (Polhill et al. 2001; Gotts et al. 2003), the second a model of the stock market (LeBaron et al. 1999). The first example demonstrates how branching statements with floating point operands of comparison operators create a high degree of nonlinearity, leading in this case to the creation of 'ghost' agents -- visible to some parts of the program but not to others. A potential solution to this problem is proposed. The second example shows how mathematical descriptions of models in the literature are insufficient to enable exact replication of work since mathematically equivalent implementations in terms of real number arithmetic are not equivalent in terms of floating point arithmetic.

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

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

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

Inter-Organizational Learning and Collective Memory in Small Firms Clusters: an Agent-Based Approach

Francesca Borrelli, Cristina Ponsiglione, Luca Iandoli and Giuseppe Zollo
Journal of Artificial Societies and Social Simulation 8 (3) 4

Kyeywords: Firm Networks, Collective Memory, Agent Based Models, Uncertainty
Abstract: Literature about Industrial Districts has largely emphasized the importance of both economic and social factors in determining the competitiveness of these particular firms\' clusters. For thirty years, the Industrial District productive and organizational model represented an alternative to the integrated model of fordist enterprise. Nowadays, the district model suffers from competitive gaps, largely due to the increase of competitive pressure of globalization. This work aims to analyze, through an agent-based simulation model, the influence of informal socio-cognitive coordination mechanisms on district\'s performances, in relation to different competitive scenarios. The agent-based simulation approach is particularly fit for this purpose as it is able to represent the Industrial District\'s complexity. Furthermore, it permits to develop dynamic analysis of district\'s performances according to different types of environment evolution. The results of this work question the widespread opinion that cooperative districts can answer to environmental changes more effectively that non-cooperative ones. In fact, the results of simulations show that, in the presence of turbulent scenarios, the best performer districts are those in which cooperation and competition, trust and opportunism balance out.

Is Your Model Susceptible to Floating-Point Errors?

Luis R. Izquierdo and Gary Polhill
Journal of Artificial Societies and Social Simulation 9 (4) 4

Kyeywords: Floating Point Arithmetic, Floating Point Errors, Agent Based Modelling, Computer Modelling, Replication
Abstract: This paper provides a framework that highlights the features of computer models that make them especially vulnerable to floating-point errors, and suggests ways in which the impact of such errors can be mitigated. We focus on small floating-point errors because these are most likely to occur, whilst still potentially having a major influence on the outcome of the model. The significance of small floating-point errors in computer models can often be reduced by applying a range of different techniques to different parts of the code. Which technique is most appropriate depends on the specifics of the particular numerical situation under investigation. We illustrate the framework by applying it to six example agent-based models in the literature.

Information Feedback and Mass Media Effects in Cultural Dynamics

Juan Carlos González-Avella, Mario G. Cosenza, Konstantin Klemm, Víctor M. Eguíluz and Maxi San Miguel
Journal of Artificial Societies and Social Simulation 10 (3) 9

Kyeywords: Agent Based Model, Culture, Dissemination, Mass Media
Abstract: We study the effects of different forms of information feedback associated with mass media on an agent-agent based model of the dynamics of cultural dissemination. In addition to some processes previously considered, we also examine a model of local mass media influence in cultural dynamics. Two mechanisms of information feedback are investigated: (i) direct mass media influence, where local or global mass media act as an additional element in the network of interactions of each agent, and (ii) indirect mass media influence, where global media acts as a filter of the influence of the existing network of interactions of each agent. Our results generalize substantiate previous findings showing that cultural diversity builds-up by increasing the strength of the mass media influence. We find that this occurs independently of the mechanisms of action (direct or indirect) of the mass media message. However, through an analysis of the full range of parameters measuring cultural diversity, we establish that the enhancement of cultural diversity produced by interaction with mass media only occurs for strong enough mass media messages. In comparison with previous studies a main different result is that weak mass media messages, in combination with agent-agent interaction, are efficient in producing cultural homogeneity. Moreover, the homogenizing effect of weak mass media messages are more efficient for direct local mass media messages than for global mass media messages or indirect global mass media influences.

Groups of Agents with a Leader

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

Spatial Dynamics of Pandemic Influenza in a Massive Artificial Society

Phillip Stroud, Sara Del Valle, Stephen Sydoriak, Jane Riese and Susan Mniszewski
Journal of Artificial Societies and Social Simulation 10 (4) 9

Kyeywords: Agent Based Modeling, Computer Simulation, Epidemic Simulation, Public Health Policy
Abstract: EpiSimS is a massive simulation of the movements, activities, and social interactions of individuals in realistic synthetic populations, and of the dynamics of contagious disease spread on the resulting social contact network. This paper describes the assumptions and methodology in the EpiSimS model. It also describes and presents a simulation of the spatial dynamics of pandemic influenza in an artificial society constructed to match the demographics of southern California. As an example of the utility of the massive simulation approach, we demonstrate a strong correlation between local demographic characteristics and pandemic severity, which gives rise to previously unanticipated spatial pandemic hotspots. In particular, the average household size in a census tract is strongly correlated with the clinical attack rate computed by the simulation. Public heath agencies with responsibility for communities having relatively high population per household should expect to be more severely hit by a pandemic.

How to Choose the Bidding Strategy in Continuous Double Auctions: Imitation Versus Take-The-Best Heuristics

Marta Posada and Adolfo López-Paredes
Journal of Artificial Societies and Social Simulation 11 (1) 6

Kyeywords: Agent Based Models, Double Auction, Individual and Social Learning, Computational Organization, Bounded Rationality
Abstract: Human-subject market experiments have established in a wide variety of environments that the Continuous Double Auction (CDA) guarantees the maximum efficiency (100 percent) and the transaction prices converge quickly to the competitive equilibrium price. Since in human-subject experiments we can not control the agents\' behaviour, one would like to know if these properties (quick price convergence and high market efficiency) hold for alternative agents\' bidding strategies. We go a step farther: we substitute human agents by artificial agents to calibrate the agents\' behaviour . In this paper we demonstrate that price convergence and allocative market efficiency in CDA markets depend on the proportion of the bidding strategies (Kaplan, Zero-Intelligence Plus, and GD) that agents have on both market sides. As a result, price convergence may not be achieved. The interesting question to ask is: can convergence be assured if the agents choose their bidding strategies? Since humans are frugal we explore two fast & frugal heuristics (imitation versus take-the-best) to choose one of three bidding strategies in order to answer this question. We find that the take-the-best choice performs much better than the imitation heuristic in the three market environments analyzed. Our experiment can be interpreted as a test to see whether an individual learning outperforms social learning or individual rationality (take-the-best) outperforms ecological rationality (imitation), for a given relevant institution (the CDA) in alternative environments.

REsCape: an Agent-Based Framework for Modeling Resources, Ethnicity, and Conflict

Ravi Bhavnani, Dan Miodownik and Jonas Nart
Journal of Artificial Societies and Social Simulation 11 (2) 7

Kyeywords: Agent-Based Model, Ethnicity, Salience, Polarization, Domination, Civil War, Greed, Natural Resources
Abstract: This research note provides a general introduction to REsCape: an agent-based computational framework for studying the relationship between natural resources, ethnicity, and civil war. By permitting the user to specify: (i) different resource profiles ranging from a purely agrarian economy to one based on the artisanal or industrial extraction of alluvial or kimberlite diamonds; (ii) different patterns of ethnic domination, ethnic polarization, and varying degrees of ethnic salience; as well as (iii) specific modes of play for key agents, the framework can be used to assess the effects of key variables — whether taken in isolation or in various combinations — on the onset and duration of civil war. Our objective is to make REsCape available as an open source toolkit in the future, one that can be used, modified, and refined by students and scholars of civil war.

A Framework for Megascale Agent Based Model Simulations on Graphics Processing Units

Mikola Lysenko and Roshan M. D'Souza
Journal of Artificial Societies and Social Simulation 11 (4) 10

Kyeywords: GPGPU, Agent Based Modeling, Data Parallel Algorithms, Stochastic Simulations
Abstract: Agent-based modeling is a technique for modeling dynamic systems from the bottom up. Individual elements of the system are represented computationally as agents. The system-level behaviors emerge from the micro-level interactions of the agents. Contemporary state-of-the-art agent-based modeling toolkits are essentially discrete-event simulators designed to execute serially on the Central Processing Unit (CPU). They simulate Agent-Based Models (ABMs) by executing agent actions one at a time. In addition to imposing an un-natural execution order, these toolkits have limited scalability. In this article, we investigate data-parallel computer architectures such as Graphics Processing Units (GPUs) to simulate large scale ABMs. We have developed a series of efficient, data parallel algorithms for handling environment updates, various agent interactions, agent death and replication, and gathering statistics. We present three fundamental innovations that provide unprecedented scalability. The first is a novel stochastic memory allocator which enables parallel agent replication in O(1) average time. The second is a technique for resolving precedence constraints for agent actions in parallel. The third is a method that uses specialized graphics hardware, to gather and process statistical measures. These techniques have been implemented on a modern day GPU resulting in a substantial performance increase. We believe that our system is the first ever completely GPU based agent simulation framework. Although GPUs are the focus of our current implementations, our techniques can easily be adapted to other data-parallel architectures. We have benchmarked our framework against contemporary toolkits using two popular ABMs, namely, SugarScape and StupidModel.

Homo Socionicus: a Case Study of Simulation Models of Norms

Martin Neumann
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.

Governments, Civilians, and the Evolution of Insurgency: Modeling the Early Dynamics of Insurgencies

D. Scott Bennett
Journal of Artificial Societies and Social Simulation 11 (4) 7

Kyeywords: Agent Based Models, Insurgency, Dynamics, Civil War
Abstract: This paper models the early dynamics of insurgency using an agent-based computer simulation of civilians, insurgents, and soldiers. In the simulation, insurgents choose to attack government forces, which then strike back. Such government counterattacks may result in the capture or killing of insurgents, may make nearby civilians afraid to become insurgents, but may also increase the anger of surrounding civilians if there is significant collateral damage. If civilians become angry enough, they become new insurgents. I simulate the dynamics of these interactions, focusing on the effectiveness of government forces at capturing insurgents vs. their accuracy in avoiding collateral damage. The simulations suggest that accuracy (avoidance of collateral damage) is more important for the long-term defeat of insurgency than is effectiveness at capturing insurgents in any given counterattack. There also may be a critical 'tipping point' for accuracy below which the length of insurgencies increases dramatically. The dynamics of how insurgencies grow or decline in response to various combinations of government accuracy and effectiveness illustrate the tradeoffs faced by governments in dealing with the early stages of an insurgency.

A Proximate Mechanism for Communities of Agents to Commemorate Long Dead Ancestors

Bill Tomlinson
Journal of Artificial Societies and Social Simulation 12 (1) 7

Kyeywords: Agent Based Models, Ancestor Commemoration, Dominance Relationships, Communication, Cooperation, Memory
Abstract: Many human cultures engage in the collective commemoration of dead members of their community. Ancestor veneration and other forms of commemoration may help to reduce social distance within groups, thereby encouraging reciprocity and providing a significant survival advantage. Here we present a simulation in which a prototypical form of ancestor commemoration arises spontaneously among computational agents programmed to have a small number of established human capabilities. Specifically, ancestor commemoration arises among agents that: a) form relationships with each other, b) communicate those relationships to each other, and c) undergo cycles of life and death. By demonstrating that ancestor commemoration could have arisen from the interactions of a small number of simpler behavioural patterns, this simulation may provide insight into the workings of human cultural systems, and ideas about how to study ancestor commemoration among humans.

A Spatial Agent-Based Model of N-Person Prisoner's Dilemma Cooperation in a Socio-Geographic Community

Conrad Power
Journal of Artificial Societies and Social Simulation 12 (1) 8

Kyeywords: Agent Based Modeling, Cooperation, Prisoners Dilemma, Spatial Interaction Model, Spatially Structured Social Dilemma, Geographic Information Systems
Abstract: The purpose of this paper is to present a spatial agent-based model of N-person prisoner's dilemma that is designed to simulate the collective communication and cooperation within a socio-geographic community. Based on a tight coupling of REPAST and a vector Geographic Information System, the model simulates the emergence of cooperation from the mobility behaviors and interaction strategies of citizen agents. To approximate human behavior, the agents are set as stochastic learning automata with Pavlovian personalities and attitudes. A review of the theory of the standard prisoner's dilemma, the iterated prisoner's dilemma, and the N-person prisoner's dilemma is given as well as an overview of the generic architecture of the agent-based model. The capabilities of the spatial N-person prisoner's dilemma component are demonstrated with several scenario simulation runs for varied initial cooperation percentages and mobility dynamics. Experimental results revealed that agent mobility and context preservation bring qualitatively different effects to the evolution of cooperative behavior in an analyzed spatial environment.

Contra Epstein, Good Explanations Predict

Nicholas S. Thompson and Patrick Derr
Journal of Artificial Societies and Social Simulation 12 (1) 9

Kyeywords: ABM, Agent Based Model, Modeling, Prediction, Explanation, Philosophy of Science
Abstract: Epstein has argued that an explanation\'s capacity to make predictions should play a minor role in its evaluation . This view contradicts centuries of scientific practice and, at least, decades of philosophy of science. We argue that the view is not only unfounded but seems to arise from a mistaken fear that ABM models are in need of defense against the criticism that they don\'t necessarily forecast events in the natural or social world.

Tools of the Trade: A Survey of Various Agent Based Modeling Platforms

Cynthia Nikolai and Gregory Madey
Journal of Artificial Societies and Social Simulation 12 (2) 2

Kyeywords: Agent Based Modeling, Individual Based Model, Multi Agent Systems
Abstract: Agent Based Modeling (ABM) toolkits are as diverse as the community of people who use them. With so many toolkits available, the choice of which one is best suited for a project is left to word of mouth, past experiences in using particular toolkits and toolkit publicity. This is especially troublesome for projects that require specialization. Rather than using toolkits that are the most publicized but are designed for general projects, using this paper, one will be able to choose a toolkit that already exists and that may be built especially for one's particular domain and specialized needs. In this paper, we examine the entire continuum of agent based toolkits. We characterize each based on 5 important characteristics users consider when choosing a toolkit, and then we categorize the characteristics into user-friendly taxonomies that aid in rapid indexing and easy reference.

How Groups Can Foster Consensus: The Case of Local Cultures

Patrick Groeber, Frank Schweitzer and Kerstin Press
Journal of Artificial Societies and Social Simulation 12 (2) 4

Kyeywords: Social Norms, Conventions, Bounded Confidence, Dynamic Networks
Abstract: A local culture denotes a set of rules on business behaviour among firms in a cluster. Similar to social norms or conventions, it is an emergent feature of interaction in an economic network. To model its emergence, we consider a distributed agent population, representing cluster firms. Further, we build on a continuous opinion dynamics model with bounded confidence (ε), which assumes that two agents only interact if differences in their behaviour are less than ε. Interaction results in more similarity of behaviour, i.e. convergence towards a common mean. Two aspects extend this framework: (i) The agent\'s in-group consisting of acquainted interaction partners is explicitly taken into account, leading to an effective agent behaviour as agents try to continue to interact with past partners and thus seek to stay sufficiently close to them. (ii) The in-group network structure changes over time, as agents form new links to other agents with sufficiently close effective behaviour or delete links to agents no longer close in behaviour. Thus, the model introduces a feedback mechanism of agent behaviour and in-group structure. Studying its consequences by means of agent-based computer simulations, we find that for narrow-minded agents (low ε) the feedback mechanism helps find consensus more often, whereas for open-minded agents (high ε) this does not necessarily hold. Overall, the dynamics of agent interaction in clusters as modelled here, are conducive to consensus among all or a majority of agents.

An Analysis of the Insertion of Virtual Players in GMABS Methodology Using the Vip-JogoMan Prototype

Diana Adamatti, Jaime Simão Sichman and Helder Coelho
Journal of Artificial Societies and Social Simulation 12 (3) 7

Kyeywords: Role-Playing Games, Multi-Agent Based Simulation, Natural Resources, Virtual Players
Abstract: The GMABS (Games and Multi-Agent-Based Simulation) methodology was created from the integration of RPG and MABS techniques. This methodology links the dynamic capacity of MABS (Multi-Agent-Based Simulation) and the discussion and learning capacity of RPG (Role-Playing Games). Using GMABS, we have developed two prototypes in the natural resources management domain. The first prototype, called JogoMan (Adamatti et. al, 2005), is a paper-based game: all players need to be physically present in the same place and time, and there is a minimum needed number of participants to play the game. In order to avoid this constraint, we have built a second prototype, called ViP-JogoMan (Adamatti et. al, 2007), which is an extension of the first one. This second game enables the insertion of virtual players that can substitute some real players in the game. These virtual players can partially mime real behaviors and capture autonomy, social abilities, reaction and adaptation of the real players. We have chosen the BDI architecture to model these virtual players, since its paradigm is based on folk psychology; hence, its core concepts easily map the language that people use to describe their reasoning and actions in everyday life. ViP-JogoMan is a computer-based game, in which people play via Web, players can be in different places and it does not have a hard constraint regarding the minimum number of real players. Our aim in this paper is to present some test results obtained with both prototypes, as well as to present a preliminary discussion on how the insertion of virtual players has affected the game results.

Large Scale Daily Contacts and Mobility Model - an Individual-Based Countrywide Simulation Study for Poland

Franciszek Rakowski, Magdalena Gruziel, Michal Krych and Jan P Radomski
Journal of Artificial Societies and Social Simulation 13 (1) 13

Kyeywords: Agent Based Model, Educational Availability, Daily Commuting, Social Network, Virtual Society Simulations
Abstract: In this study we describe a simulation platform used to create a virtual society of Poland, with a particular emphasis on contact patterns arising from daily commuting to schools or workplaces. In order to reproduce the map of contacts, we are using a geo-referenced Agent Based Model. Within this framework, we propose a set of different stochastic algorithms, utilizing available aggregated census data. Based on this model system, we present selected statistical analysis, such as the accessibility of schools or the location of rescue service units. This platform will serve as a base for further large scale epidemiological and transportation simulation studies. However, the first approach to a simple, country-wide transportation model is also presented here. The application scope of the platform extends beyond the simulations of epidemic or transportation, and pertains to any situation where there are no easily available means, other than computer simulations, to conduct large scale investigations of complex population dynamics.

Social Preference, Incomplete Information, and the Evolution of Ultimatum Game in the Small World Networks: An Agent-Based Approach

Bo Xianyu
Journal of Artificial Societies and Social Simulation 13 (2) 7

Kyeywords: Spatial Ultimatum Game, Complex Network, Social Preference, Agent Based Modeling
Abstract: Certain social preference models have been proposed to explain fairness behavior in experimental games. Existing bodies of research on evolutionary games, however, explain the evolution of fairness merely through the self-interest agents. This paper attempts to analyze the ultimatum game's evolution on complex networks when a number of agents display social preference. Agents' social preference is modeled in three forms: fairness consideration or maintaining a minimum acceptable money level, inequality aversion, and social welfare preference. Different from other spatial ultimatum game models, the model in this study assumes that agents have incomplete information on other agents' strategies, so the agents need to learn and develop their own strategies in this unknown environment. Genetic Algorithm Learning Classifier System algorithm is employed to address the agents' learning issue. Simulation results reveal that raising the minimum acceptable level or including fairness consideration in a game does not always promote fairness level in ultimatum games in a complex network. If the minimum acceptable money level is high and not all agents possess a social preference, the fairness level attained may be considerably lower. However, the inequality aversion social preference has negligible effect on the results of evolutionary ultimatum games in a complex network. Social welfare preference promotes the fairness level in the ultimatum game. This paper demonstrates that agents' social preference is an important factor in the spatial ultimatum game, and different social preferences create different effects on fairness emergence in the spatial ultimatum game.

Leadership in Small Societies

Stephen Younger
Journal of Artificial Societies and Social Simulation 13 (3) 5

Kyeywords: Leadership, Reciprocity, Pacific Island Societies, Norms
Abstract: Multi-agent simulation was used to study several styles of leadership in small societies. Populations of 50 and100 agents inhabited a bounded landscape containing a fixed number of food sources. Agents moved about the landscape in search of food, mated, produced offspring, and died either of hunger or at a predetermined maximum age. Leadership models focused on the collection and redistribution of food. The simulations suggest that individual households were more effective at meeting their needs than a simple collection-redistribution scheme. Leadership affected the normative makeup of the population: altruistic leaders caused altruistic societies and demanding leaders caused aggressive societies. Specific leadership styles did not provide a clear advantage when two groups competed for the same resources. The simulation results are compared to ethnographic observations of leadership in Pacific island societies.

Obligation Norm Identification in Agent Societies

Tony Bastin Roy Savarimuthu, Stephen Cranefield, Maryam A. Purvis and Martin K. Purvis
Journal of Artificial Societies and Social Simulation 13 (4) 3

Kyeywords: Norms, Social Norms, Obligations, Norm Identification, Agent-Based Simulation, Simulation of Norms, Artificial Societies, Normative Multi-Agent Systems (NorMAS)
Abstract: Most works on norms have investigated how norms are regulated using institutional mechanisms. Very few works have focused on how an agent may infer the norms of a society without the norm being explicitly given to the agent. This paper describes a mechanism for identifying one type of norm, an obligation norm. The Obligation Norm Inference (ONI) algorithm described in this paper makes use of an association rule mining approach to identify obligation norms. Using agent based simulation of a virtual restaurant we demonstrate how an agent can identify the tipping norm. The experiments that we have conducted demonstrate that an agent in the system is able to add, remove and modify norms dynamically. An agent can also flexibly modify the parameters of the system based on whether it is successful in identifying a norm.

Dilbert-Peter Model of Organization Effectiveness: Computer Simulations

Pawel Sobkowicz
Journal of Artificial Societies and Social Simulation 13 (4) 4

Kyeywords: Organization Productivity, Peter Principle, Agent Based Modeling
Abstract: We describe a computer model of general effectiveness of a hierarchical organization depending on two main aspects: effects of promotion to managerial levels and efforts to self-promote of individual employees, reducing their actual productivity. The combination of judgment by appearance in the promotion to higher levels of hierarchy and the Peter Principle (which states that people are promoted to their level of incompetence) results in fast declines in effectiveness of the organization. The model uses a few synthetic parameters aimed at reproduction of realistic conditions in typical multilayer organizations. It is shown that improving organization resiliency to self-promotion and continuity of individual productiveness after a promotion can greatly improve the overall organization effectiveness.

ODD Updated

Gary Polhill
Journal of Artificial Societies and Social Simulation 13 (4) 9

Kyeywords: ODD, Individual Based Models, Agent Based Models, Replication, Documentation
Abstract: An update to Volker Grimm and colleagues\' Overview, Design concepts and Details (ODD) protocol for documenting individual and agent based models (I/ABM) has recently been published in Ecological Modelling. This renames the \'State variables and scales\' element to \'Entities, state variables and scales\', and the \'Input\' element to \'Input data\', introduces two new Design concepts (\'Basic principles\' and \'Learning\'), and renames another (\'Fitness\' is now generalised to \'Objectives\'). The Design concepts element can now also be shortened such that it is not required to include any design concept that is irrelevant to the model, and expanded to include new design concepts more appropriate to the model being described. Other clarifications of intentions in the original protocol have been made.

The ABM Template Models: A Reformulation with Reference Implementations

Alan G. Isaac
Journal of Artificial Societies and Social Simulation 14 (2) 5

Kyeywords: Template Models, Reference Implementations, Spatially-Situated Agents, Spatially Distributed Resources
Abstract: We refine a prominent set of template models for agent-based modeling, and we offer new reference implementations. We also address some issues of design, flexibility, and ease of use that are relevant to the choice of an agent-based modeling platform.

The Current State of Normative Agent-Based Systems

Christopher D. Hollander and Annie S. Wu
Journal of Artificial Societies and Social Simulation 14 (2) 6

Kyeywords: Norms, Normative Agents, Agents, Agent-Based System, Agent-Based Simulation, Agent-Based Modeling
Abstract: Recent years have seen an increase in the application of ideas from the social sciences to computational systems. Nowhere has this been more pronounced than in the domain of multiagent systems. Because multiagent systems are composed of multiple individual agents interacting with each other many parallels can be drawn to human and animal societies. One of the main challenges currently faced in multiagent systems research is that of social control. In particular, how can open multiagent systems be configured and organized given their constantly changing structure? One leading solution is to employ the use of social norms. In human societies, social norms are essential to regulation, coordination, and cooperation. The current trend of thinking is that these same principles can be applied to agent societies, of which multiagent systems are one type. In this article, we provide an introduction to and present a holistic viewpoint of the state of normative computing (computational solutions that employ ideas based on social norms.) To accomplish this, we (1) introduce social norms and their application to agent-based systems; (2) identify and describe a normative process abstracted from the existing research; and (3) discuss future directions for research in normative multiagent computing. The intent of this paper is to introduce new researchers to the ideas that underlie normative computing and survey the existing state of the art, as well as provide direction for future research.

Science as a Social System and Virtual Research Environment

Sergey Parinov and Cameron Neylon
Journal of Artificial Societies and Social Simulation 14 (4) 10

Kyeywords: Virtual Research Environment, Science System Social Sustainability, Agent Based Modeling
Abstract: The accumulation of gradual changes in scientific landscape and research practice due to the Internet has the potential to enhance the quality of both cognitive and social aspects of science and scientists. New types of research outputs, modes of scientific communication and new circulation mechanisms, as well as enhanced opportunities for scientific re-use and measuring research impact, in combination with new approaches to research assessment and evaluation are all having profound effects on the social system of science. To be sure that these innovations will not break the social sustainability of the science community, it will be valuable to develop a model of science as a tool for computer simulation of social consequences from possible innovations within virtual research environment. Focusing on possible social problems related to these new virtual research environments this short paper provides a brief analysis of the current situation in science (challenges, problems, main actors), general views on model of science (landscape, main agents, important properties, etc.) and on areas where simulation can contribute to better understanding of possible futures for the scientific community.

Social Simulation That 'Peers into Peer Review'

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.

Rethinking the Tragedy of the Commons: The Integration of Socio-Psychological Dispositions

Julia Schindler
Journal of Artificial Societies and Social Simulation 15 (1) 4

Kyeywords: Agent-Based Model, Common-Pool Resources, Behavioral Game Theory, Nash Equilibria, Nash Extension NetLogo, Socio-Psychological Dispositions, Tragedy of the Commons
Abstract: In current research there is increasing evidence on why and how common-pool resources are successfully, i.e. sustainably, managed without the force of (often unsuccessful) top-level policy regulations. G. Hardin argued in 1968 in his Tragedy of the Commons (Hardin 1968) that commons must become depleted if users are free to choose extraction and resource use levels. In this study, we propose that socio-psychological factors can explain the success of resource use of a common without any top-level regulations. We exemplify this behavior by a spatio-temporally dynamic agent-based model of the Tragedy of the Commons using behavioral game theory and Nash equilibria calculation. By providing a spatio-temporal representation of Hardin's dilemma, the model could verify his argument in a temporal way if socio-psychological influence is disregarded, and indicated that under its influence the common can be sustained. We illustrated how dispositions such as cooperativeness, positive reciprocity, fairness towards others, and risk aversion broadly can support sustainable use, while negative reciprocity, fairness towards oneself, and conformity can inhibit it. Though, we also showed that it would be dangerous to generalize this kind of behavior, as changes in one of these dispositions can result in opposite system behavior, in dependence on the other dispositions. Due to this general capacity to account for such complex behavior that real common-pool system usually exhibit, and its ability to model intermediate equilibria, the proposed modelling approach, i.e. combining game-theory solution concepts with agent-based modelling, may be worth an assessment of its capacity to model empirical phenomena.

Thomas C. Schelling and the Computer: Some Notes on Schelling's Essay "On Letting a Computer Help with the Work"

Rainer Hegselmann
Journal of Artificial Societies and Social Simulation 15 (4) 9

Kyeywords: Schelling Model, Segregation, Configuration Game, History of Computational Social Science, Agent Based Modeling
Abstract: Today the Schelling model is a standard component in introductory courses to agent-based modelling and simulation. When Schelling presented his model in the years between 1969 and 1978, his own analysis was based on manual table top exercises. Even more, Schelling explicitly warned against using computers for the analysis of his model. That is puzzling. A resolution to that puzzle can be found in an essay that Schelling wrote as teaching material for his students. That essay is now published by Schelling in JASSS, exactly 40 years after it was written. In his essay, Schelling gives a guided tour of a computer implementation of his model he himself implemented, de-spite his warnings. On this tour, though more in passing, Schelling gives hints to an extremely generalised version of his model. My article explains why we find the gen-eralised version of Schelling's model on the tour through his computer program rather than in his published articles.

An Agent Based Model of Monopolistic Competition in International Trade with Emerging Firm Heterogeneity

Ermanno Catullo
Journal of Artificial Societies and Social Simulation 16 (2) 7

Kyeywords: International Trade, Agent Based Model, Firm Heterogeneity
Abstract: Export firms have better performance than firms that do not export, the so-called exporter premia: exporters are larger, they are relatively more capital and skill intensive, exporters have higher productivity (Bernard et al. 2007a; Bernard et al. 2005). The better performance of exporters may be the result of a self-selection effect: only the most competitive firms are able to enter foreign markets (ex-ante self-selection). On the other hand, exporting may improve firm performance (ex-post effect). Differences between exporters and non-exporters may have a significant impact on aggregate welfare and growth; in particular, disentangling the importance of the ex-ante effect from the ex-post effect may be useful for designing public policies (Bernard & Jensen 1999). The economic approach based on the Melitz (2003) model analyzes the exporter premia using monopolistic competition markets with firm heterogeneity in terms of a given distribution of firm productivity. This paper presents an agent based simulation of a monopolistic competition market in which firm heterogeneity is an emerging pattern of firms' choices and interactions, conceiving productivity growth as the results of firms' individual innovative efforts. The model is able to replicate the better performance of exporters, stressing the importance of decision-making processes and learning capabilities of firms in determining both the ex-ante and the ex-post effects.

Modelling the Economy as an Agent-Based Process: ABCE, A Modelling Platform and Formal Language for ACE

Davoud Taghawi-Nejad
Journal of Artificial Societies and Social Simulation 16 (3) 1

Kyeywords: Agent Based Modeling, Macoeconomics, Ontology, Economics, Process, Platform
Abstract: In this paper, I argue that the key innovation of Agent-Based Economics is not the introduction of the individual agent as an ontological object, but the fact that the economy is modelled as a process. I propose a formal language to express economic models as processes. This formal language leads to ABCE, a modelling platform for Agent-Based Economic models. ABCE's core idea is that the modeller specifies the decisions of the agents, the order of actions, the goods and their physical transformation (the production and the consumption functions). Actions, such as production and consumption, interactions and exchange, are handled automatically by the modelling platform, when the agent decided to do them. The result is a program where *the source code contains only economically meaningful commands*. Beyond the decisions and the setup, ABCE handles everything in the background. It scales on multi-core computers and cloud computing services, without the intervention of the modeler. ABCE is based on python, a language which is characterized by highly readable code.

Segregated Cooperation

Roger Waldeck
Journal of Artificial Societies and Social Simulation 16 (4) 14

Kyeywords: Social Emotions, Norms, Prisoner, Spatial Interaction Structures, Segregation, Agent-Based Simulation
Abstract: Observations in experiments show that players in a prisoner's dilemma may adhere more or less to a cooperative norm. Adherence is defined by the intensity of pro-social emotions, like guilt, of deviating from the norm. Players consider also payoffs from defection as a motive to deviate. By combining both incentives, the modeling may explain conditional cooperation and the existence of polymorphic equilibria in which cooperators and defectors coexist. We then show by the use of simulations, that local interaction structures may produce segregation and the appearance of cooperative zones under these conditions.

The Evolution of Multiple Resistant Strains: An Abstract Model of Systemic Treatment and Accumulated Resistance

Benjamin D. Nye
Journal of Artificial Societies and Social Simulation 16 (4) 2

Kyeywords: Evolution, Acquired Resistance, Agent Based Modeling, Selection Pressure, SIS Model, PS-I
Abstract: The proliferation of resistant strains has been an unintended side effect of human interventions designed to eliminate unwanted elements of our environment. Any attempt to destroy an adaptive population must also be considered as a selection pressure, so that the most resistant members will comprise the next generation. Procedures have been developed to slow the evolution of resistances in a population, with the most common approaches being overkill and treatment cycling. This paper presents an agent-based Susceptible-Infection-Susceptible (SIS) model to explore the effectiveness of these procedures on an abstract epidemic of pathogens, focusing on how the interaction between interventions and mutations affects acquired resistance. Illustrative findings indicate that overkill performed better than cycling treatments when variation in resistances had a high degree of heritability. When resistance variation was effectively memoryless, cycling and overkill performed comparably. However, overkill was prone to backlash outliers where an amplification of infection resistance occurred- a significant drawback to the overkill technique. These backlash events indicate that cycling interventions might be more effective when variation is memoryless and carrying resistance incurs a cost to overall fitness. However, under limited fitness-cost conditions explored, cycling performed no better than overkill for preventing resistance.

Modelling Tourism in the Galapagos Islands: An Agent-Based Model Approach

Francesco Pizzitutti, Carlos F. Mena and Stephen J. Walsh
Journal of Artificial Societies and Social Simulation 17 (1) 14

Kyeywords: Spatial Agent Based Model and Simulation, Galapagos Islands, Tourist Destination Dynamics
Abstract: Currently tourism is the main driver of change in the Galapagos Islands, affecting the social, terrestrial, and marine sub-systems. Tourism also has direct and indirect consequences for the unique archipelago’s natural habitats and for the human well-being. Describing the mechanisms that drive and affect most the tourism development in Galapagos is a preliminary condition to developing a better understanding of the interaction structure of factors that shape the Galapagos archipelago as a social-ecological complex system. In this paper, we present a first attempt to represent the touristic market in Galapagos trough an Agent Based Model (ABM) of touristic activity, focusing on touristic offers, reservations, and touristic activities. The model is based on an individual-based representation of tourists’ consumption preferences and touristic accommodation offers in the Galapagos Islands. Tourist agents are created to mimic the real world by assigning average characteristics of individuals who visit the Galapagos Archipelago of Ecuador. The accommodation offers (i.e., hotels and cruises) are generated in accordance with actual conditions derived from data collected through field surveys. The model includes a market agent that can change the prices, create and delete accommodation offers following an evolutionary algorithm. We carried out preliminary simulations that show a close agreement between real world data and model outputs. Furthermore we used the model to generate three “what if” scenarios in order to study how emergent patterns in the touristic market in Galapagos are affected by changes in the archipelago environment. In this way we illustrate how the model can be used as a useful tool to help public policy makers to explore the consequences of their decisions.

Parental Choices and Children’s Skills: An Agent-Based Model of Parental Investment Behavior and Skill Inequality Within and Across Generations

Andrés Cardona
Journal of Artificial Societies and Social Simulation 17 (4) 8

Kyeywords: Skill Formation, Parental Investments, Inequality in the Life Course, Intrahousehold Allocation of Resources, Agent Behavior
Abstract: An agent-based simulation model (ABM) is developed and implemented using Python to explore the emergence of intragenerational and intergenerational skill inequality at the societal level that results from differences in parental investment behavior at the household level during early stages of the life course. Parental behavior is modeled as optimal, heuristic-based, or norm-oriented. Skills grow according to the technology of skill formation developed in the field of economics, calibrated with empirically estimated parameters from existing research. Agents go through a simplified life course. During childhood and adolescence, skills are produced through parental investments. In adulthood, individuals find a partner, give birth to the next generation, and invest in offspring. Number and spacing of children and available resources are treated as exogenous factors and are varied experimentally. Simulation experiments suggest that parental decisions at the household level play a role in the emergence of inequality at the societal level. Being egalitarian or not is the most important distinction in parental investment behavior, while optimizing parents generate similar results as egalitarian parents. Furthermore, there is a tradeoff between equality at home and inequality at the macro-level. Changes in the environment reduce or exacerbate inequality depending on parental investment behavior. One prediction of the model on intragenerational inequality in cognitive skills was validated with the use of empirical data. The simulation can best be described as a middle-range model, informed by research on skill formation and the intrahousehold allocation of resources. It is a first step toward more complex ABMs on inequality from a life course perspective. Possible model extensions are suggested. The Overview, Design Concepts, and Details (ODD) protocol and Design of Experiments (DOE) were used to document the model and set up the experimental design respectively.

Self-Policing Through Norm Internalization: A Cognitive Solution to the Tragedy of the Digital Commons in Social Networks

Daniel Villatoro, Giulia Andrighetto, Rosaria Conte and Jordi Sabater-Mir
Journal of Artificial Societies and Social Simulation 18 (2) 2

Kyeywords: Self-Organisation, Norms, Emergent Behavior, Cognitive Modelling, Artificial Social Systems
Abstract: In the seminal work "An Evolutionary Approach to Norms", Axelrod identified internalization as one of the key mechanisms that supports the spreading and stabilization of norms. But how does this process work? This paper advocates a rich cognitive model of different types, degrees and factors of norm internalization. Rather than a none-or-all phenomenon, we claim that norm internalization is a dynamic process, whose deepest step occurs when norms are complied with thoughtlessly. In order to implement a theoretical model of internalization and check its effectiveness in sustaining social norms and promoting cooperation, a simulated web-service distributed market has been designed, where both services and agents' tasks are dynamically assigned. Internalizers are compared with agents whose behaviour is driven only by self-interested motivations. Simulation findings show that in dynamic unpredictable scenarios, internalizers prove more adaptive and achieve higher level of cooperation than agents whose decision-making is based only on utility calculation.

The Big Impact of Small Groups on College Drinking

Ben Fitzpatrick, Jason Martinez, Elizabeth Polidan and Ekaterini Angelis
Journal of Artificial Societies and Social Simulation 18 (3) 4

Kyeywords: Group Formation, Peer Influence, Identity Control Theory, Social Norms, College Drinking
Abstract: College drinking is a problem with severe academic, health, and safety consequences. The underlying social processes that lead to increased drinking activity are not well understood. Social Norms Theory is an approach to analysis and intervention based on the notion that students’ misperceptions about the drinking culture on campus lead to increases in alcohol use. In this paper we develop an agent-based simulation model, implemented in MATLAB, to examine college drinking. Students’ drinking behaviors are governed by their identity (and how others perceive it) as well as peer influences, as they interact in small groups over the course of a drinking event. Our simulation results provide some insight into the potential effectiveness of interventions such as social norms marketing campaigns.

The Effects of Network Structure on the Emergence of Norms in Adaptive Populations

Peter Revay
Journal of Artificial Societies and Social Simulation 18 (4) 14

Kyeywords: Social Norms, Agent-Based Modeling, Social Networks, Neighborhood Structure, Cooperation
Abstract: The different ways individuals socialize with others affect the conditions under which social norms are able to emerge. In this work an agent-based model of cooperation in a population of adaptive agents is presented. The model has the ability to implement a multitude of network topologies. The agents possess strategies represented by boldness and vengefulness values in the spirit of Axelrod's (1986) norms game. However, unlike in the norms game, the simulations abandon the evolutionary approach and only follow a single-generation of agents who are nevertheless able to adapt their strategies based on changes in their environment. The model is analyzed for potential emergence or collapse of norms under different network and neighborhood configurations as well as different vigilance levels in the agent population. In doing so the model is found able to exhibit interesting emergent behavior suggesting potential for norm establishment even without the use of so-called metanorms. Although the model shows that the success of the norm is dependent on the neighborhood size and the vigilance of the agent population, the likelihood of norm collapse is not monotonically related to decreases in vigilance.

"Anarchy" Reigns: A Quantitative Analysis of Agent-Based Modelling Publication Practices in JASSS, 2001-2012

Simon Angus and Behrooz Hassani-Mahmooei
Journal of Artificial Societies and Social Simulation 18 (4) 16

Kyeywords: Agent Based Modelling, Social Sciences, Simulation, Publishing
Abstract: Agent Based Modelling (ABM), a promising scientific toolset, has received criticism from some, in part, due to a claimed lack of scientific rigour, especially in the communication of its methods and results. To test the veracity of these claims, we conduct a structured analysis of over 900 scientific objects (figures, tables, or equations) that arose from 128 ABM papers published in the Journal of Artificial Societies and Social Simulation (JASSS), during the period 2001 to 2012 inclusive. Regrettably, we find considerable evidence in support of the detractors of ABM as a scientific enterprise: elementary plotting attributes are left off more often than not; basic information such as the number of replicates or the basis behind a particular statistic are not included; and few, if any, established methodological communication standards are apparent. In short, 'anarchy reigns'. Whilst the study was confined only to ABM papers of JASSS, we conclude that if the ABM community wishes its approach to be accepted further afield, authors, reviewers, and editors should take the results of our work as a wake-up call.

Emergence and Collapse of the Norm of Resource Sharing Around Locally Abundant Resources

Shiro Horiuchi
Journal of Artificial Societies and Social Simulation 18 (4) 7

Kyeywords: Agent Based Model, Resources, Norms, Hawk-Dove-Bourgeois Game
Abstract: How do individuals resolve conflicts over resources? One way is to share resources, which is possible between known individuals, with the use of sanctions on free riders or by partner selection. Another way is for anonymous individuals to respect the finders’ ownership of resources based on asymmetry and avoid conflicts over resources. This study elucidates the conditions under which anonymous individuals share resources with each other irrespective of their asymmetry with regard to resources. High resource values inhibit anonymous individuals from sharing resources; however, small cumulative values and local distributions let anonymous individuals share the resources. Punishment of the richest individuals also supports resource sharing. These conditions may represent resource sharing among anonymous individuals in periods of great disasters and may be the origin of the practice of exchange in prehistoric times.

Long Term Impacts of Bank Behavior on Financial Stability. an Agent Based Modeling Approach

Ilker Arslan, Eugenio Caverzasi, Mauro Gallegati and Alper Duman
Journal of Artificial Societies and Social Simulation 19 (1) 11

Kyeywords: Agent Based Modeling, Credit Networks, Financial Stability
Abstract: This paper presents an agent-based model aiming to shed light on the potential destabilizing effects of bank behavior. Our work takes its motivation from the effects of the financial crisis which erupted in 2007 in the US. It draws on the Financial Instability Hypothesis by Hyman P. Minsky, and on the Agent Based macro modeling literature (Delli Gatti et al. 2010, Riccetti et. al 2013) to model a simplified economy in which heterogeneous banks and firms interact on game theoretic rules. Simulation results suggest that aggregate financial instability may emerge as the outcome of banks’ attempt to increase their profit or market share through their pricing strategies. A further finding from the model is the need for banks to take into account time consistency when issuing credit in order to protect the financial stability of the system.

Simulating Trends in Artificial Influence Networks

Hannah Übler and Stephan Hartmann
Journal of Artificial Societies and Social Simulation 19 (1) 2

Kyeywords: ABM, Norms, Social Influence
Abstract: We present a study of the spreading of trends in artificial social influence networks using agent based models. We concentrate on basic properties of the agents which describe their individual attitudes towards a trend, as well as the influence which they exert in their social neighbourhood. Using a simple random network, we investigate the impact of network dynamicity, situations of opposing trends, and the disappearance of trends. A 'community' network is used to study the impact of group cohesiveness and connectors for the spreading of trends in social communities.

Oscillatory Patterns in the Amount of Demand for Dental Visits: An Agent Based Modeling Approach

Maryam Sadeghipour, Peyman Shariatpanahi, Afshin Jafari, Mohammad Hossein Khosnevisan and Arezoo Ebn Ahmady
Journal of Artificial Societies and Social Simulation 19 (3) 10

Kyeywords: Dental Health Care, Dental Routine Visit, Oscillatory Patterns, Agent Based Modeling, Google Trends
Abstract: There are some empirical evidences indicating that there is a collective complex oscillatory pattern in the amount of demand for dental visit at society level. In order to find the source of the complex cyclic behavior, we develop an agent-based model of collective behavior of routine dental check-ups in a social network. Simulation results show that demand for routine dental check-ups can follow an oscillatory pattern and the pattern’s characteristics are highly dependent upon the structure of the social network of potential patients, the population, and the number of effective contacts between individuals. Such a cyclic pattern has public health consequences for patients and economic consequences for providers. The amplitude of oscillations was analyzed under different scenarios and for different network topologies. This allows us to postulate a simulation-based theory for the likelihood observing and the magnitude of a cyclic demand. Results show that in case of random networks, as the number of contacts increases, the oscillatory pattern reaches its maximum intensity, for any population size. In case of ring lattice networks, the amplitude of oscillations reduces considerably, when compared to random networks, and the oscillation intensity is strongly dependent on population. The results for small world networks is a combination of random and ring lattice networks. In addition, the simulation results are compared to empirical data from Google Trends for oral health related search queries in different United States cities. The empirical data indicates an oscillatory behavior for the level of attention to dental and oral health care issues. Furthermore, the oscillation amplitude is correlated with town’s population. The data fits the case of random networks when the number of effective contacts is about 4-5 for each person. These results suggest that our model can be used for a fraction of people deeply involved in Internet activities like Web-based social networks and Google search.

A Heuristic Combinatorial Optimisation Approach to Synthesising a Population for Agent Based Modelling Purposes

Nam Huynh, Johan Barthelemy and Pascal Perez
Journal of Artificial Societies and Social Simulation 19 (4) 11

Kyeywords: Synthetic Population, Combinatorial Optimisation, Sample-Free, Agent Based Modelling, Social Behaviours
Abstract: This paper presents an algorithm that follows the sample-free approach to synthesise a population for agent based modelling purposes. This algorithm is among the very few in the literature that do not rely on a sample survey data to construct a synthetic population, and thus enjoy a potentially wider applications where such survey data is not available or inaccessible. Different to existing sample-free algorithms, the population synthesis presented in this paper applies the heuristics to part of the allocation of synthetic individuals into synthetic households. As a result the iterative process allocating individuals into households, which normally is the most computationally demanding and time consuming process, is required only for a subset of synthetic individuals. The population synthesiser in this work is therefore computational efficient enough for practical application to build a large synthetic population (many millions) for many thousands target areas at the smallest possible geographical level. This capability ensures that the geographical heterogeneity of the resulting synthetic population is best preserved. The paper also presents the application of the new method to synthesise the population for New South Wales in Australia in 2006. The resulting total synthetic population has approximately 6 million people living in over 2.3 million households residing in private dwellings across over 11000 Census Collection Districts. Analyses show evidence that the synthetic population matches very well with the census data across seven demographics attributes that characterise the population at both household level and individual level.

Social Dynamics of Littering and Adaptive Cleaning Strategies Explored Using Agent-Based Modelling

Ruggero Rangoni and Wander Jager
Journal of Artificial Societies and Social Simulation 20 (2) 1

Kyeywords: Littering, Goal Frame Theory, Tipping Point, Norms
Abstract: In this paper we explore how social influence may cause a non-linear transition from a clean to a littered environment, and what strategies are effective in keeping a street clean. To study this, we first implement the Goal Framing Theory of Lindenberg and Steg (2007) in an agent based model. Next, using empirical data from a field study we parameterise the model so we can replicate the results from a field study. Following that, we explore how different cleaning strategies perform. The results indicate that an adaptive/dynamical cleaning regime is more effective and cheaper than pre-defined cleaning schedules.

Enhancing the Realism of Simulation (EROS): On Implementing and Developing Psychological Theory in Social Simulation

Wander Jager
Journal of Artificial Societies and Social Simulation 20 (3) 14

Kyeywords: Psychology, Theory, Needs, Norms, Cognition, Attitudes
Abstract: Using psychological theory in agent formalisations is relevant to capture behavioural phenomena in simulation models (Enhance Realism Of Simulation - EROS). Whereas the potential contribution of psychological theory is important, also a number of challenges and problems in doing so are discussed. Next examples of implementations of psychological theory are being presented, ranging from simple implementations (KISS) of rather isolated theories to extended models that integrate different theoretical perspectives. The role of social simulation in developing dynamic psychological theory and integrated social psychological modelling is discussed. We conclude with some fundamental limitations and challenges concerning the modelling of human needs, cognition and behaviour.

Growing Unpopular Norms

Christoph Merdes
Journal of Artificial Societies and Social Simulation 20 (3) 5

Kyeywords: Social Norms, Agent-Based Simulation, Social Influence, Pluralistic Ignorance
Abstract: Unpopular norms are a pervasive and puzzling phenomenon of the social world. They are norms that are established and maintained against the interest of their subjects, but without external coercion. Pluralistic ignorance has been suggested as a potential explanation of unpopular norms. What is currently lacking is a formal model of this process that can be meaningfully compared with empirically known properties of pluralistic ignorance. An agent-based model of a growing social network can reproduce the most significant qualitative features, viz a deviation of the perceived norm from the preference distribution and the dynamical lag of the former behind the latter. In addition, the model is extended with a central influence representing for example central media or a powerful political elite.

Social Norms and the Dominance of Low-Doers

Carlo Proietti and Antonio Franco
Journal of Artificial Societies and Social Simulation 21 (1) 6

Kyeywords: Agent-Based Model, Social Norms, Game Theory
Abstract: Social norms play a fundamental role in holding groups together. The rationale behind most of them is to coordinate individual actions into a beneficial societal outcome. However, there are cases where pro-social behavior within a community seems, to the contrary, to cause inefficiencies and suboptimal collective outcomes. An explanation for this is that individuals in a society are of different types and their type determines the norm of fairness they adopt. Not all such norms are bound to be beneficial at the societal level. When individuals of different types meet a clash of norms can arise. This, in turn, can determine an advantage for the “wrong” type. We show this by a game-theoretic analysis in a very simple setting. To test this result - as well as its possible remedies - we also devise a specific simulation model. Our model is written in NETLOGO and is a first attempt to study our problem within an artificial environment that simulates the evolution of a society over time.

Modelling Sustainability Transitions: An Assessment of Approaches and Challenges

Jonathan Köhler, Fjalar de Haan, Georg Holtz, Klaus Kubeczko, Enayat Moallemi, George Papachristos and Émile Chappin
Journal of Artificial Societies and Social Simulation 21 (1) 8

Kyeywords: Transitions Models, Qualitative System Change, Modelling Social Values and Norms, Behavioural Change
Abstract: Transition modelling is an emerging but growing niche within the broader field of sustainability transitions research. The objective of this paper is to explore the characteristics of this niche in relation to a range of existing modelling approaches and literatures with which it shares commonalities or from which it could draw. We distil a number of key aspects we think a transitions model should be able to address, from a broadly acknowledged, empirical list of transition characteristics. We review some of the main strands in modelling of socio-technological change with regards to their ability to address these characteristics. These are: Eco-innovation literatures (energy-economy models and Integrated Assessment Models), evolutionary economics, complex systems models, computational social science simulations using agent based models, system dynamics models and socio-ecological systems models. The modelling approaches reviewed can address many of the features that differentiate sustainability transitions from other socio-economic dynamics or innovations. The most problematic features are the representation of qualitatively different system states and of the normative aspects of change. The comparison provides transition researchers with a starting point for their choice of a modelling approach, whose characteristics should correspond to the characteristics of the research question they face. A promising line of research is to develop innovative models of co-evolution of behaviours and technologies towards sustainability, involving change in the structure of the societal and technical systems.

Countries as Agents in a Global-Scale Computational Model

Harold J. Walbert, James L. Caton and Julia R. Norgaard
Journal of Artificial Societies and Social Simulation 21 (3) 4

Kyeywords: Agent Based Modeling, Conflict Resolution, Tribute, Diplomacy, War, Economic Analysis of Conflict
Abstract: Our agent-based model examines the ramifications of formal defense agreements between countries. Our model builds on previous work and creates an empirically based version of a tribute model in which actors within existing real-world networks demand tribute from one another. If the threatened actor does not pay the tribute, the aggressing actor will engage in a decision to start a war. Tribute and war payments are based on a measure of the country's wealth. We utilize the Correlates of War dataset to provide us with worldwide historical defense alliance information. Using these networks as our initial conditions, we run the model forward from four prominent historical years and simulate the interactions that take place as well as the changes in overall wealth. Agents in the model employ a cost benefit analysis in their decision of whether or not to go to war. This model provides results that are in qualitative agreement with historical emergent macro outcomes seen over time.

Opinion Dynamics Model Based on Cognitive Biases of Complex Agents

Pawel Sobkowicz
Journal of Artificial Societies and Social Simulation 21 (4) 8

Kyeywords: Opinion Change, Motivated Reasoning, Confirmation Bias, Complex Agents, Agent Based Model
Abstract: We present an introduction to a novel way of simulating individual and group opinion dynamics, taking into account how various sources of information are filtered due to cognitive biases. The agent-based model presented here falls into the ‘complex agent’ category, in which the agents are described in considerably greater detail than in the simplest ‘spinson’ model. To describe agents’ information processing, we introduced mechanisms of updating individual belief distributions, relying on information processing. The open nature of this proposed model allows us to study the effects of various static and time-dependent biases and information filters. In particular, the paper compares the effects of two important psychological mechanisms: confirmation bias and politically motivated reasoning. This comparison has been prompted by recent experimental psychology work by Dan Kahan. Depending on the effectiveness of information filtering (agent bias), agents confronted with an objective information source can either reach a consensus based on truth, or remain divided despite the evidence. In general, this model might provide understanding into increasingly polarized modern societies, especially as it allows us to mix different types of filters: e.g., psychological, social, and algorithmic.

Application Independent Heuristic Data Merging Methodology for Sample-Free Agent Population Synthesis

Bhagya N. Wickramasinghe
Journal of Artificial Societies and Social Simulation 22 (1) 5

Kyeywords: Agent Based Modelling, Synthetic Population Reconstruction, Heuristic Population Construction, Sample Free, Integrating Models, Iterative Proportional Fitting
Abstract: This work proposes a novel application independent heuristics specifying framework and a household structures construction process, for sample-free population synthesis. The framework decouples heuristics and the algorithm by defining a set of generic constructs to specify heuristics on relationships and household structures. The algorithm uses Iterative Proportional Fitting, Monte Carlo sampling and combinatorial optimisation to synthesise the population. Decoupled nature of the system allows it to be used in different applications relatively easily by changing the heuristics. We demonstrate that this is a robust technique capable of producing synthetic agent populations highly consistent to input data distributions using two case studies. Apart from contributing to synthetic population reconstruction, this work will form one of the building blocks for integrating independently developed models to build complex new agent based models.

The Value of Values and Norms in Social Simulation

Rijk Mercuur, Virginia Dignum and Catholijn Jonker
Journal of Artificial Societies and Social Simulation 22 (1) 9

Kyeywords: Human Values, Norms, Ultimatum Game, Empirical Data, Agent-Based Model
Abstract: Social simulations gain strength when agent behaviour can (1) represent human behaviour and (2) be explained in understandable terms. Agents with values and norms lead to simulation results that meet human needs for explanations, but have not been tested on their ability to reproduce human behaviour. This paper compares empirical data on human behaviour to simulated data on agents with values and norms in a psychological experiment on dividing money: the ultimatum game. We find that our agent model with values and norms produces aggregate behaviour that falls within the 95% confidence interval wherein human behaviour lies more often than other tested agent models. A main insight is that values serve as a static component in agent behaviour, whereas norms serve as a dynamic component.

Models Within Models – Agent-Based Modelling and Simulation in Energy Systems Analysis

Martin Klein, Ulrich J. Frey and Matthias Reeg
Journal of Artificial Societies and Social Simulation 22 (4) 6

Kyeywords: Agent Based Modelling, Computational Economics, Energy Systems Analysis, Modelling Guidelines, Policy Modelling, Energy Scenarios
Abstract: This paper tries to show the various roles agent-based modeling and simulation (ABMS) can play in technology and policy assessment of energy systems. We examine the advantages of ABMS methods using three case studies of electricity market models as example (AMIRIS, EMLab-Generation and PowerACE). In particular, we argue why ABMS might serve as framework for many future energy system models that integrate many different algorithms. We then discuss practical and theoretical problems in the development, validation and assessment of energy-system-analytical ABMS and conclude with an outlook and recommendations for energy system modellers who consider incorporating ABMS into their modelling toolbox.

Price Formation in Parallel Trading Systems: Evidence from the Fine Wine Market

Marcin Czupryna, Michał Jakubczyk and Paweł Oleksy
Journal of Artificial Societies and Social Simulation 23 (3) 11

Kyeywords: Parallel Trading, Trading Systems, Price Formation, Wine Investment, Agent Based Modelling
Abstract: What drives the prices of fine wines is not easy to discern, in view of a multitude of confounding factors characterising the transactions across several markets. At the same time, understanding the quantitative relationships and mechanisms that determine the price level is important for policy making (e.g. predicting the outcomes of regulations) and methodological purposes (which elements to consider in modelling these markets). We examine the price formation of fine wines simultaneously across three markets: an automated electronic exchange (Liv-ex), intermediated auctions, and over-the-counter (OTC). We use a unique dataset consisting of 99,769 price data points for Premier Cru Bordeaux fine wines and we examine the price determinants with Bayesian modelling. We ascertain the mean price ranking (OTC market being the most expensive and Liv-ex the least, differing by about 4.5% and -0.8% from the auctions). We also find a slight price decrease for larger transactions (approx.~0.3% reduction for a 10% volume increase) and some platykurtosis in price distribution (greatest in Liv-ex), and observe the most stochastic noise in auctions. In an agent-based simulation, we discover that it is necessary to include trading mechanisms, commissions, and OTC market heterogeneity to reproduce the observed characteristics. Our results indicate which elements should be included in future fine wine markets models.

Agent-Based Modelling of Values: The Case of Value Sensitive Design for Refugee Logistics

Christine Boshuijzen-van Burken, Ross Gore, Frank Dignum, Lamber Royakkers, Phillip Wozny and F. LeRon Shults
Journal of Artificial Societies and Social Simulation 23 (4) 6

Kyeywords: Agent Based Model, Value Sensitive Design, Simulation and Policy, Humanitarian Logistics, Refugees, Schwartz Values
Abstract: We have used value sensitive design as a method to develop an agent-based model of values in humanitarian logistics for refugees. Schwartz's theory of universal values is implemented in the model in such a way that agents can make value trade-offs, which are operationalized into a measure of refugee wellbeing and a measure of public opinion about how the refugee logistics is being handled. By trying out different ‘value-scenarios’, stakeholders who are responsible for, or involved in refugee logistics can have insights into the effects of various value choices. The model is visualized and made usable as a platform (interactive website) for decision-makers to understand the trade-offs in policies for government and non-government organizations.

Modeling Interaction in Collaborative Groups: Affect Control Within Social Structure

Nikolas Zöller, Jonathan H. Morgan and Tobias Schröder
Journal of Artificial Societies and Social Simulation 24 (4) 6

Kyeywords: Agent Based Modeling, Affect Control Theory, Expectation States Theory, Networks, Online Collaboration, Group Dynamics
Abstract: This paper studies the dynamics of identity and status management within groups in collaborative settings. We present an agent-based simulation model for group interaction rooted in social psychological theory. The model integrates affect control theory with networked interaction structures and sequential behavior protocols as they are often encountered in task groups. By expressing status hierarchy through network structure, we build a bridge between expectation states theory and affect control theory, and are able to reproduce central results from the expectation states research program in sociological social psychology. Furthermore, we demonstrate how the model can be applied to analyze specialized task groups or sub-cultural domains by combining it with empirical data sources. As an example, we simulate groups of open-source software developers and analyze how cultural expectations influence the occupancy of high status positions in these groups.