32 articles matched your search for
Self-Organisation, Norms, Emergent Behavior, Cognitive Modelling, Artificial Social Systems
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.
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.
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.
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?
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.
Rob E.J.R. Koper
Journal of Artificial Societies and Social Simulation 8 (2) 5
Kyeywords: Self-Organisation, Education, Distance Learning, Lifelong Learning, Learning Network
Abstract: A learning network is a network of persons who create, share, support and study units of learning (courses, workshops, lessons, etc.) in a specific knowledge domain. Such networks may consist of a large number of alternative units of learning. One of the problems learners face in a learning network is to select the most suitable path through the units of learning in order to build the required competence in an effective and efficient way. This study explored the use of indirect social interaction to solve this problem. Units of learning that have been completed successfully by other comparable learners are presented to the learners as navigational support. A learning network is simulated in which learners search for, enrol in and study units of learning, subject to a variety of constraints: a) variable quality of the different units of learning, b) disturbance, i.e. interference by priorities other than learning and c) matching errors that occur when the entry requirements of the selected unit of learning do not align with the pre-knowledge of the learner. Two conditions are explored in the network: the selection of units of learning with and without indirect social interaction. It was found that indirect social interaction increases the proportion of learners who attain their required competence in the simulated learning network.
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.
Thomas Malsch and Ingo Schulz-Schaeffer
Journal of Artificial Societies and Social Simulation 10 (1) 11
Kyeywords: Socionics, Sociology, Multi-Agent Systems, Artificial Social Systems, Hybrid Systems, Social Simulation
Abstract: Socionics is an interdisciplinary approach with the objective to use sociological knowledge about the structures, mechanisms and processes of social interaction and social communication as a source of inspiration for the development of multi-agent systems, both for the purposes of engineering applications and of social theory construction and social simulation. The approach has been spelled out from 1998 on within the Socionics priority program funded by the German National research foundation. This special issue of the JASSS presents research results from five interdisciplinary projects of the Socionics program. The introduction gives an overview over the basic ideas of the Socionics approach and summarizes the work of these projects.
Michael Köhler, Roman Langer, Rolf von Lüde, Daniel Moldt, Heiko Rölke and Rüdiger Valk
Journal of Artificial Societies and Social Simulation 10 (1) 3
Kyeywords: Multi-Agents Systems, Petri Nets, Self-Organisation, Social Theories
Abstract: This contribution summarises the core results of the transdisciplinary ASKO project, part of the German DFG's programme Sozionik, which combines sociologists' and computer scientists' skills in order to create improved theories and models of artificial societies. Our research group has (a) formulated a social theory, which is able to explain fundamental mechanisms of self-organisation in both natural and artificial societies, (b) modelled this in a mathematical way using a visual formalism, and (c) developed a novel multi-agent system architecture which is conceptually coherent, recursively structured (hence non-eclectic) and based on our social theory. The article presents an outline of both a sociological middle-range theory of social self-organisation in educational institutions, its formal, Petri net based model, including a simulation of one of its main mechanisms, and the multi-agent system architecture SONAR. It describes how the theory was created by a re-analysis of some grand social theories, by grounding it empirically, and finally how the theory was evaluated by modelling its concepts and statements.
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.
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.
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.
Kees Zoethout, Wander Jager and Eric Molleman
Journal of Artificial Societies and Social Simulation 13 (3) 7
Kyeywords: Task Allocation, Group Processes, Psychological Theory, Small Groups, Self-Organisation
Abstract: This paper describes how a work group and a newcomer mutually adapt. We study two types of simulated groups that need an extra worker, one group because a former employee had left the group and one group because of its workload. For both groups, we test three conditions, newcomers being specialists, newcomers being generalists, and a control condition with no newcomer. We hypothesise that the group that needs an extra worker because of its workload will perform the best with a newcomer being a generalist. The group that needs an extra worker because a former employee had left the group, will perform better with a specialist newcomer. We study the development of task allocation and performance, with expertise and motivation as process variables. We use two performance indicators, the performance time of the slowest agent that indicates the speed of the group and the sum of performance of all agents to indicate labour costs. Both are indicative for the potential benefit of the newcomer. Strictly spoken the results support our hypotheses although the differences between the groups with generalists and specialists are negligible. What really mattered was the possibility for a newcomer to fit in.
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.
Shah Jamal Alam, Armando Geller, Ruth Meyer and Bogdan Werth
Journal of Artificial Societies and Social Simulation 13 (4) 6
Kyeywords: Cognition, Contextualized Reasoning, Evidence-Driven Agent-Based Social Simulation, Empirical Agent-Based Social Simulation, Rich Cognitive Modelling, Tzintzuntzan
Abstract: In many computational social simulation models only cursory reference to the foundations of the agent cognition used is made and computational expenses let many modellers chose simplistic agent cognition architectures. Both choices run counter to expectations framed by scholars active in the domain of rich cognitive modelling that see agent reasoning as socially inherently contextualized. The Manchester school of social simulation proposed a particular kind of a socially contextualized reasoning mechanism, so called endorsements, to implement the cognitive processes underlying agent action selection that eventually causes agent interaction. Its usefulness lies in its lightweight architecture and in taking into account folk psychological conceptions of how reasoning works. These and other advantages make endorsements an amenable tool in everyday social simulation modelling. A yet outstanding comprehensive introduction to the concept of endorsements is provided and its theoretical basis is extended and extant research is critically reviewed. Improvements to endorsements regarding memory and perception are suggested and tested against a case-study.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Valentina Y. Guleva, Klavdiya O. Bochenina, Maria V. Skvorcova and Alexander V. Boukhanovsky
Journal of Artificial Societies and Social Simulation 20 (4) 15
Kyeywords: Interbank Network, Emergent Behavior, Topology Formation, Temporal Network, Complex System, Simulation Tool
Abstract: The topology of the interbank market plays a crucial role during a crisis, affecting the spreading or absorption of financial shock. The structure of an interbank network changes in the process of its evolution because of the interbank interactions and the interactions between banks and customers. To simulate a temporal interbank network, it is necessary to set an initial state and an evolution law for the topology and system entities. Because of the complex interplay between the network topology and the bank states, the stability of a temporal interbank network is generally unpredictable, even if all parameters and rules of interactions are known. In this paper, we present a simulation tool for temporal interbank networks aimed at exploring the different drivers contributing to evolutionary dynamics of banking networks. We describe a general-simulation scheme for temporal interbank networks and incorporate the creation and rewiring of edges because of the counter-party choices with the deletion of nodes and edges in case of a bank default. An example of the implementation of the general scheme is also presented and include models of banks and customers, strategies of counter-party choice, and clearing algorithms. To perform a qualitative and quantitative study of the evolutionary process, the proposed simulation tool supports the calculation of different topological and stability metrics and visualization of network evolution. The experimental study demonstrates (i) an illustrative example of the application of the simulation tool for synthetic networks while varying the counter-party choice policies and parameters of nodes and edges, and (ii) an investigation of the computational complexity and scalability of the simulation scheme.
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.
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.
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.
Toby Pilditch and Jens Koed Madsen
Journal of Artificial Societies and Social Simulation 24 (1) 5
Kyeywords: Micro-Targeted Campaigning, Cognitive Modelling, Source Credibility, Political Messaging, Simulation, Bayesian Modelling
Abstract: The use of data to inform and run political campaigning has become an inescapable trend in recent years. In attempting to persuade an electorate, micro-targeted campaigns (MTCs) have been employed to great effect through the use of tailored messaging and selective targeting. Here we investigate the capacity of MTCs to deal with the diversity of political preferences across an electorate. More precisely, via an Agent-Based Model we simulate various diverse electorates that encompass single issue, multiple issue, swing, and disengaged voters (among others, including combinations thereof) and determine the relative persuasive efficacy of MTCs when pitted against more traditional, population-targeting campaigns. Taking into account the perceived credibility of these campaigns, we find MTCs highly capable of handling greater voter complexity than shown in previous work, and yielding further advantages beyond traditional campaigns in their capacity to avoid inefficient (or even backfiring) interactions – even when fielding a low credibility candidate.
Shaoni Wang, Kees Zoethout, Wander Jager and Yanzhong Dang
Journal of Artificial Societies and Social Simulation 24 (4) 9
Kyeywords: Individual Needs, Motivation, Group Performance, Self-Organisation, Task Allocation, Agent-Based Modelling
Abstract: Team performance can be considered a macro-level outcome that depends on three sets of micro-level factors: individual workers contributing to the task, team composition, and task characteristics. For a number of reasons, the complex dynamics between individuals in the task allocation process are difficult to systematically explore in traditional experimental settings: the motivational dynamics, the complex dynamics of task allocation processes, and the lack of experimental control over team composition imply an ABM-approach being more feasible. For this reason, we propose an updated version of the WORKMATE model that has been developed to explore the dynamics of team performance. In doing so, we added Deci and Ryan’s SDT theory, stating that people are motivated by three psychological needs, competence, autonomy, and belongingness. This paper is aimed at explaining the architecture of the model, and some first simulation runs as proof of concept. The experimental results show that: 1) an appropriate motivation threshold will help the team have the lowest performance time; 2) the time needed for the task allocation process is related to the importance of different motivations; 3) highly satisfied teams are more likely composed of members valuing autonomy.