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25 articles matched your search for the keywords:
Qualitative, Evidence, Narrative, Specification, Quantitative, Formal

Qualitative Modeling and Simulation of Socio-Economic Phenomena

Giorgio Brajnik and Marji Lines
Journal of Artificial Societies and Social Simulation 1 (1) 2

Kyeywords: Qualitative Modeling, Qualitative Reasoning, Decision Making, Allocation
Abstract: This paper describes an application of recently developed qualitative reasoning techniques to complex, socio-economic allocation problems. We explain why we believe traditional optimization methods are inappropriate and how qualitative reasoning could overcome some of these shortcomings. A case study is presented where an authority is expected to devise a policy that satisfies certain constraints. We describe how sets of rules of thumb implementing such a policy can be analyzed and validated by the decision maker using a program which automatically builds and simulates qualitative models of the underlying dynamical system. Such a program constructs and simulates models from incomplete descriptions of initial states and functional relationships between variables. We show that it nevertheless gives sufficient information to the decision maker.

Narrative Intelligence from the Bottom Up: a Computational Framework for the Study of Story-Telling in Autonomous Agents

Kerstin Dautenhahn and Steve Coles
Journal of Artificial Societies and Social Simulation 4 (1) 1

Kyeywords: Autobiographic Agents, Narrative Intelligence, Autonomous Robots
Abstract: This paper addresses Narrative Intelligence from a bottom up, Artificial Life perspective. First, different levels of narrative intelligence are discussed in the context of human and robotic story-tellers. Then, we introduce a computational framework which is based on minimal definitions of stories, story-telling and autobiographic agents. An experimental test-bed is described which is applied to the study of story-telling, using robotic agents as examples of situated, autonomous minimal agents. Experimental data are provided which support the working hypothesis that story-telling can be advantageous, i.e. increases the survival of an autonomous, autobiographic, minimal agent. We conclude this paper by discussing implications of this approach for story-telling in humans and artifacts.

Pair Interactions: Real and Perceived Attitudes

David Pearson and Marie-Reine Boudarel
Journal of Artificial Societies and Social Simulation 4 (4) 4

Kyeywords: Quantitative socio-dynamics, attitudes, self-confidence
Abstract: In this article we look at how a social interaction model can be developed that takes into account the influence that perceived attitudes can have on the resulting dynamics. The model is based on a pair interaction situation and a master equation approach. The model can be easily programmed using standard high level simulation languages. Some simulation studies are presented in the article.

Reasoning About Other Agents: a Plea for Logic-Based Methods

Wendelin Reich
Journal of Artificial Societies and Social Simulation 7 (4) 4

Kyeywords: Formal Logic, Social Interaction, Social Simulation, Agents, Social Meta-Reasoning, Reasoning About Reasoning
Abstract: Formal logic has become an invaluable tool for research on multi-agent systems, but it plays a minor role in the more applied field of agent-based social simulation (ABSS). We argue that logical languages are particularly useful for representing social meta-reasoning, that is, agents' reasoning about the reasoning of other agents. After arguing that social meta-reasoning is a frequent and important social phenomenon, we present a set of general criteria (functional completeness, understandability, changeability, and implementability/executability) to compare logic to two alternative formal methods: black box techniques (e.g., neural networks) and decision-theoretical models (e.g., game theory). We then argue that in terms of functional completeness, understandability and changeability, logical representations of social meta-reasoning compare favorably to these two alternatives.

Formal Systems and Agent-Based Social Simulation Equals Null?

Maria Fasli
Journal of Artificial Societies and Social Simulation 7 (4) 7

Kyeywords: Formal Systems, Social Interactions, Social Agents, Commitments, Roles, Obligations
Abstract: This paper discusses some of the merits of the use of formal logic in multi-agent systems and agent-based simulation research. Reasons for the plethora of formal systems are discussed as well as how formal systems and agent-based social simulation can work together. As an example a formal system for describing social relationships and interactions in a multi-agent system is presented and how this could benefit from agent-based social simulation as well as make a contribution is discussed.

The Use of Logic in Agent-Based Social Simulation

Frank Dignum, Bruce Edmonds and Liz Sonenberg
Journal of Artificial Societies and Social Simulation 7 (4) 8

Kyeywords: Logic, Agent Technology, Formal Systems, Social Theory
Abstract: [No abstract for this editorial]

Integrated Description and Qualitative Simulation Method for Group Behavior

Bin Hu and Xia Gongcheng
Journal of Artificial Societies and Social Simulation 8 (2) 1

Kyeywords: Group Behaviour, Qualitative Simulation, QSIM, Causal Graph, Group Dynamics
Abstract: This paper presents a qualitative simulation method for analyzing employee group behavior by integrating QSIM (Qualitative SIMulation) with basic causal reasoning. A description method for complex interactions between environment, management policy and group behaviour is designed. A qualitative simulation method including the simulation rules and a simulation engine is then proposed. The validation of the proposed method is tested, and an example is given of how this method can be applied to the development of management policy for the effective motivation of employees. Simulation results show that this method can be used to explain and predict changes in group behavior, and also to aid in decision making on employee group management.

A Formal Model for the Fifth Discipline

Lourival Paulino da Silva
Journal of Artificial Societies and Social Simulation 8 (3) 6

Kyeywords: Multi-Agent Systems, Formal Methods, the Fifth Discipline, Organizational Modeling, Learning Organization, Organizational Learning, z
Abstract: In this paper we present the main results of our research concerning the development of a formal model for the theory called The Fifth Discipline. Our model is based on a Multi-Agent Systems framework. The contributions of this work include a formal model for the Fifth Discipline, and analyses that highlight key features of that theory, namely the pressupositions that agents must be honest, cooperative, tenacious, and that trust is fundamental in the agents' interactions.

Towards Good Social Science

Scott Moss and Bruce Edmonds
Journal of Artificial Societies and Social Simulation 8 (4) 13

Kyeywords: Methodology, Agent Based Social Simulation, Qualitative Analysis; Evidence; Conditions of Application; History of Science
Abstract: The paper investigates what is meant by "good science" and "bad science" and how these differ as between the natural (physical and biological) sciences on the one hand and social sciences on the other. We conclude on the basis of historical evidence that the natural science are much more heavily constrained by evidence and observation than by theory while the social sciences are constrained by prior theory and hardly at all by direct evidence. Current examples of the latter proposition are taken from recent issues of leading social science journals. We argue that agent based social simulations can be used as a tool to constrain the development of a new social science by direct (what economists dismiss as anecdotal) evidence and that to do so would make social science relevant to the understanding and influencing of social processes. We argue that such a development is both possible and desirable. We do not argue that it is likely.

On the Simulation of Global Reputation Systems

Andreas Schlosser, Marco Voss and Lars Brückner
Journal of Artificial Societies and Social Simulation 9 (1) 4

Kyeywords: Reputation System, Trust, Formalization, Simulation
Abstract: Reputation systems evolve as a mechanism to build trust in virtual communities. In this paper we evaluate different metrics for computing reputation in multi-agent systems. We present a formal model for describing metrics in reputation systems and show how different well-known global reputation metrics are expressed by it. Based on the model a generic simulation framework for reputation metrics was implemented. We used our simulation framework to compare different global reputation systems to find their strengths and weaknesses. The strength of a metric is measured by its resistance against different threat-models, i.e. different types of hostile agents. Based on our results we propose a new metric for reputation systems.

Formal Interpretation of a Multi-Agent Society As a Single Agent

Tibor Bosse and Jan Treur
Journal of Artificial Societies and Social Simulation 9 (2) 6

Kyeywords: Collective Intelligence, Simulation, Logical Formalisation, Single Vs. Multi-Agent Behaviour
Abstract: In this paper the question is addressed to what extent the collective processes in a multi-agent society can be interpreted as single agent processes. This question is answered by formal analysis and simulation. It is shown for an example process how it can be conceptualised, formalised and simulated in two different manners: from a single agent (or cognitive) and from a multi-agent (or social) perspective. Moreover, it is shown how an ontological mapping can be formally defined between the two formalisations, and how this mapping can be extended to a mapping of dynamic properties. Thus it is shown how collective behaviour can be interpreted in a formal manner as single agent behaviour.

Cellular-Automata Based Qualitative Simulation for Nonprofit Group Behavior

Bin Hu and Debing Zhang
Journal of Artificial Societies and Social Simulation 10 (1) 1

Kyeywords: Cellular Automata; Qualitative Simulation; Group Behavior; Loyalty-Cost Equilibrium; Loyalty Gravitation; Cost Gravitation
Abstract: A cellular automata based qualitative simulation of group behavior (referred hitherto as \'loyalty to group\') will be presented by integrating QSIM (Qualitative SIMulation) and CA (Cellular Automata) modeling. First, we provide a breakdown of the structure of a group and offer an analysis of how this structure impacts behavior. The characteristics and impact had by anomalies within a group and by environmental factors are also explored. Second, we explore the transition between cause and effect (referred hitherto as the \'transition rule\') and the change in behavior that is the result of this transition (referred hitherto as the \'successor behavior state\'). A filter for weeding out anomalies is then proposed. The simulation engine is then used integrating all relevant data as outlined above. A concept referred to as the \'Loyalty-cost equilibrium\' is presented and factored into the filter. Third, the validity of this method is tested by running the simulation using eight generalized examples. The input-output of each simulation run using these examples is consistent with what can reasonably be accepted to be true, thus demonstrating that the proposed method is valid. At this point we illustrate how the simulation is applied in context. Simulation outputs (effect on group behavior) at each time stage of two alternating changes in policy are compared to determine which policy would be the most advantageous. This demonstrates that this method serves as reliable virtual tool in the decision making difficulties of group management.

The Impact of HIV/AIDS in the Context of Socioeconomic Stressors: an Evidence-Driven Approach

Shah Jamal Alam, Ruth Meyer, Gina Ziervogel and Scott Moss
Journal of Artificial Societies and Social Simulation 10 (4) 7

Kyeywords: Agent-Based Social Simulation, Evidence-Driven Modeling, Socioeconomic Stressors, HIV/AIDS Impact
Abstract: In this paper, we present an agent-based simulation model of the social impacts of HIV/AIDS in villages in the Sekhukhune district of the Limpopo province in South Africa. AIDS is a major concern in South Africa, not just in terms of disease spread but also in term of its impact on society and economic development. The impact of the disease cannot however be considered in isolation from other stresses, such as food insecurity, high climate variability, market fluctuations and variations in support from government and non-government sources. The model described in this paper focuses on decisions made at the individual and household level, based upon evidence from detailed case studies, and the different types of networks between these players that influence their decision making. Key to the model is that these networks are dynamic and co-evolving, something that has rarely been considered in social network analysis. The results presented here demonstrate how this type of simulation can aid better understanding of this complex interplay of issues. In turn, we hope that this will prove to be a powerful tool for policy development.

Modelling Opinion Formation with Physics Tools: Call for Closer Link with Reality

Pawel Sobkowicz
Journal of Artificial Societies and Social Simulation 12 (1) 11

Kyeywords: Methodology, Agent Based Social Simulation, Qualitative Analysis; Evidence; Conditions of Application
Abstract: The growing field of studies of opinion formation using physical formalisms and computer simulation based tools suffers from relative lack of connection to the 'real world' societal behaviour. Such sociophysics research should aim at explaining observations or at proposing new ones. Unfortunately, this is not always the case, as many works concentrate more on the models themselves than on the social phenomena. Moreover, the simplifications proposed in simulations often sacrifice realism on the altar of computability. There are several ways to improve the value of the research, the most important by promoting truly multidisciplinary cooperation between physicists aiming to describe social phenomena and sociologists studying the phenomena in the field. In the specific case of modelling of opinion formation there are a few technical ideas which might bring the computer models much closer to reality, and therefore to improve the predictive value of the sociophysics approach.

Bootstrapping Knowledge About Social Phenomena Using Simulation Models

Bruce Edmonds
Journal of Artificial Societies and Social Simulation 13 (1) 8

Kyeywords: Philosophy, Evolution, Selection, Standards, Epistemology, Formal Models
Abstract: There are considerable difficulties in the way of the development of useful and reliable simulation models of social phenomena, including that any simulation necessarily includes many assumptions that are not directly supported by evidence. Despite these difficulties, many still hope to develop quite general models of social phenomena. This paper argues that such hopes are ill-founded, in other words that there will be no short-cut to useful and reliable simulation models. However this paper argues that there is a way forward, that simulation modelling can be used to "boot-strap" useful knowledge about social phenomena. If each bit of simulation work can result in the rejection of some of the possible processes in observed social phenomena, even if this is about a very specific social context, then this can be used as part of a process of gradually refining our knowledge about such processes in the form of simulation models. Such a boot-strapping process will only be possible if simulation models are more carefully judged, that is a greater selective pressure is applied. In particular models which are just an analogy of social processes in computational form should be treated as "personal" rather than "scientific" knowledge. Such analogical models are useful for informing the intuition of its developers and users, but do not help the community of social simulators and social scientists to "boot-strap" reliable social knowledge. However, it is argued that both participatory modelling and evidence-based modelling can play a useful part in this process. Some kinds of simulation model are discussed with respect to their suitability for the boot-strapping of social knowledge. The knowledge that results is likely to be of a more context-specific, conditional and mundane nature than many social scientists hope for.

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

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

Kyeywords: Agent-Based Modelling, Land Use/Cover Change, Qualitative Research, Interdisciplinary Research
Abstract: This paper describes and evaluates a process of using qualitative field research data to extend the pre-existing FEARLUS agent-based modelling system through enriching its ontological capabilities, but without a deep level of involvement of the stakeholders in designing the model itself. Use of qualitative research in agent-based models typically involves protracted and expensive interaction with stakeholders; consequently gathering the valuable insights that qualitative methods could provide is not always feasible. At the same time, many researchers advocate building completely new models for each scenario to be studied, violating one of the supposed advantages of the object-oriented programming languages in which many such systems are built: that of code reuse. The process described here uses coded interviews to identify themes suggesting changes to an existing model, the assumptions behind which are then checked with respondents. We find this increases the confidence with which the extended model can be applied to the case study, with a relatively small commitment required on the part of respondents.

Modelling Contextualized Reasoning in Complex Societies with "Endorsements"

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.

Measuring Simulation-Observation Fit: An Introduction to Ordinal Pattern Analysis

Warren Thorngate and Bruce Edmonds
Journal of Artificial Societies and Social Simulation 16 (2) 4

Kyeywords: Ordinal, Goodness-Of-Fit, Statistics, Evidence, Validity, Predictions, Observations
Abstract: Most traditional strategies of assessing the fit between a simulation's set of predictions (outputs) and a set of relevant observations rely either on visual inspection or squared distances among averages. Here we introduce an alternative goodness-of-fit strategy, Ordinal Pattern Analysis (OPA) that will (we argue) be more appropriate for judging the goodness-of-fit of simulations in many situations. OPA is based on matches and mismatches among the ordinal properties of predictions and observations. It does not require predictions or observations to meet the requirements of interval or ratio measurement scales. In addition, OPA provides a means to assess prediction-observation fits case-by-case prior to aggregation, and to map domains of validity of competing simulations. We provide examples to illustrate how OPA can be employed to assess the ordinal fit and domains of validity of simulations of share prices, crime rates, and happiness ratings. We also provide a computer programme for assisting in the calculation of OPA indices.

A Context- and Scope-Sensitive Analysis of Narrative Data to Aid the Specification of Agent Behaviour

Bruce Edmonds
Journal of Artificial Societies and Social Simulation 18 (1) 17

Kyeywords: Qualitative Data, Context, Scope, Analysis, Specification, Narrative
Abstract: A structure for analysing narrative data is suggested, one that distinguishes three parts in sequence: context (a heuristic to identify what knowledge is relevant given a kind of situation), scope (what is possible within that situation) and narrative elements (the detailed conditional and sequential structure of actions and events given the context and scope). This structure is first motivated and then illustrated with some simple examples taken from Sukaina Bhawani’s thesis (Bhawani 2004). It is suggested that such a structure might be helpful in preserving more of the natural meaning of such data, as well as being a good match to a context-dependent computational architecture, and thus facilitate the process of using narrative data to inform the specification of behavioural rules in an Agent-Based Simulation. This suggestion only solves part of the “Narrative Data to Agent Behaviour” puzzle – this structure needs to be combined and improved by other methods and appropriate computational architectures designed to suit it.

Using Qualitative Evidence to Inform the Specification of Agent-Based Models

Bruce Edmonds
Journal of Artificial Societies and Social Simulation 18 (1) 18

Kyeywords: Qualitative, Evidence, Narrative, Specification, Quantitative, Formal
Abstract: This is an introduction to the special section of JASSS on the above topic. It argues for the importance of qualitative evidence in social science, and particularly in the specification of agent-based models. It ends by suggesting some criteria for judging methods for using qualitative evidence for this purpose.

Structuring Qualitative Data for Agent-Based Modelling

Amineh Ghorbani, Gerard Dijkema and Noortje Schrauwen
Journal of Artificial Societies and Social Simulation 18 (1) 2

Kyeywords: Ethnography, Institutional Analysis, Survey, Qualitative Data, MAIA, Conceptual Modelling
Abstract: Using ethnography to build agent-based models may result in more empirically grounded simulations. Our study on innovation practice and culture in the Westland horticulture sector served to explore what information and data from ethnographic analysis could be used in models and how. MAIA, a framework for agent-based model development of social systems, is our starting point for structuring and translating said knowledge into a model. The data that was collected through an ethnographic process served as input to the agent-based model. We also used the theoretical analysis performed on the data to define outcome variables for the simulation. We conclude by proposing an initial methodology that describes the use of ethnography in modelling.

Interactive Simulations with a Stylized Scale Model to Codesign with Villagers an Agent-Based Model of Bushmeat Hunting in the Periphery of Korup National Park (Cameroon)

Christophe Le Page, Kadiri Serge Bobo, Towa Olivier William Kamgaing, Bobo Fernanda Ngahane and Matthias Waltert
Journal of Artificial Societies and Social Simulation 18 (1) 8

Kyeywords: Bushmeat Hunting, Participatory Simulation, Community-Based Wildlife Management, Companion Modelling, Qualitative Data
Abstract: An agent-based model (ABM) representing snare trapping of blue duikers (Cephalophus monticola) was co-designed and used with local populations to raise their awareness about the sustainability of bushmeat hunting activities in the region of the Korup National Park (South-West Cameroon). Village meetings based on interactive simulations with a stylized scale model were structured in three successive steps. During the first step, an abstract representation of a village surrounded by a portion of forest was co-designed by directly manipulating the computer interface displaying a spatial grid. Then, knowledge about the live-cycle traits and the behavior of blue duikers was shared through the demonstration of the individual-based population dynamics module of the ABM. The objective of the second step, introducing the hunting module of the ABM, was to elicit snare trapping practices trough interactive simulation and to calibrate the hunting module by setting a value for the probability of a blue duiker to be caught by a snare trap. In a third step, a more realistic version of the ABM was introduced. The seven villages included in the process were located in the GIS-based spatial representation, and the number of “Hunter” agents for each village in the ABM was set according to the results of a survey. The demonstration of this realistic version triggered discussion about possible management scenarios, whose results obtained with the finalized version of the ABM will be discussed during next round of village meetings. We present the pros and cons of the method consisting in using at an early stage of the process interactive simulations with stylized scale models to specify empirically-based agent-based models.

Grounded Simulation

Martin Neumann
Journal of Artificial Societies and Social Simulation 18 (1) 9

Kyeywords: Grounded Theory, Evidence Based Modelling, Theoretical Coding, Ontologies, Stylized Facts, Theory Development
Abstract: This paper investigates the contribution of evidence-based modelling to grounded theory (GT). It is argued that evidence-based modelling provides additional sources to truly arrive at a theory through the inductive process of a Grounded Theory approach. This is shown by two examples. One example concerns the development of software ontologies of criminal organisations. The other example is a simulation model of escalation of ethno-nationalist conflicts. The first example concerns early to middle stages of the research process. The development of an ontology provides a tool for the process of theoretical coding in a GT approach. The second example shows stylised facts resulting from a simulation model of the escalation of ethno-nationalist conflicts in the former Yugoslavia. These reveal mechanisms of nationalist radicalisation. This provides additional credibility for the claim that evidence-based modelling assists to inductively generate a theory in a GT approach.

Simulation for Interpretation: A Methodology for Growing Virtual Cultures

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

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

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.