Agent Based Social Simulation

We give a preliminary perspective on the basic principles and pitfalls of adjustable autonomy and humancentered teamwork. We then summarize the interim results of our study on the problem of work practice modeling and human-agent collaboration in space applications, the development of a broad model of human-agent teamwork grounded in practice, and the integration of the Brahms, KAoS, and NOMADS agent frameworks We hope our work will benefit those who plan and participate in work activities in a wide variety of space applications, as well as those who are interested in design and execution tools for teams of robots that can function as effective assistants to humans.

In recent years the interdisciplinary field of Computational Social Science has developed theory and methodologies for building spatial Agent-Based Social Simulation (ABSS) models of human societies that are situated in ecosystems with land cover and climate. This article explains the needs and demand for Geographic Information Systems (GIS) in these types of agent-based models, with an emphasis on models applied to Eastern Africa and Inner Asia and relevance for understanding and analyzing development issues. The models are implemented with the MASON (Multi-Agent Simulator Of Networks and Neighborhoods) system, an open-source simulation environment in the Java language and suitable for developing ABSS models with GIS for representing spatial features.

Seasonal climate forecasts provide probabilistic information on future climate on timescales of two to three months. Where this information is not presently used it is difficult to evaluate the impact it might have. In order to justify disseminating the information to marginal groups it is important that the potential impact of the forecast is explored so that the negative and positive effects are at least partially appreciated before use of the information is widely promoted. We use an agent-based social simulation model, based on empirical evidence from field work in Lesotho, to assess the impact of using seasonal forecasts among smallholder farmers. The impact of using the forecast depends on the agents' initial household characteristics, what options they choose in responding to the forecast and the trust they place in the forecast (which in turn depends on their ability to learn and to follow their neighbours). Interaction of climate, crop productivity and social factors determines how much householdagents benefit or lose, evaluated in terms of crop yields and likelihood of exhausting food storage. Adoption of the forecast has the potential to decrease starvation among marginal household-agents but poor forecasts may do more harm than good. This work suggests that if forecasts are not correct more than 60-70% of the time, then they are unlikely to benefit * Corresponding author. Present address:

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.

Computational social science and in particular agent-based social simulation continue to gain momentum in the academic community. Social network analysis enjoys even more popularity. They both have much in common. In agent-based models, individual interactions are simulated to generate social patterns of all kinds, including relationships that can then be analyzed by social network analysis. This chapter describes and discusses the role of agent-based modeling in the generative-analytical part of this symbiosis. More precisely, ...

In this paper we compare models of two different kinds of processes in multi-agent-based social simulations (MABSS): military conflict within a states-system (GeoSim), and land use and ownership change (FEARLUS). This is a kind of model-to-model comparison which is novel within Multi-Agent Based Simulation research, although well-known within mathematics, physics and biology: comparing objects (in this case MABSS) drawn from distinct research domains, in order to draw out their structural similarities and differences. This can facilitate research in both domains, by allowing the use of findings from each to illuminate the other. Based on the similarities between FEARLUS and GeoSim, we conclude by identifying a new class of MABSS models based on territorial resource allocation processes occurring on a 2-dimensional space (which we define as the “TRAP2†class). The existence of the cross-domain TRAP2 class of models in turn suggests that MABSS researchers should look for other memb...

Traditional (i.e. analytical) modelling practices in the social sciences rely on a very well established, although implicit, methodological protocol, both with respect to the way models are presented and to the kinds of analysis that are performed. Unfortunately, computersimulated models often lack such a reference to an accepted methodological standard. This is one of the main reasons for the scepticism among mainstream social scientists that results in low acceptance of papers with agent-based methodology in the top journals. We identify some methodological pitfalls that, according to us, are common in papers employing agent-based simulations, and propose appropriate solutions. We discuss each issue with reference to a general characterization of dynamic micro models, which encompasses both analytical and simulation models. In the way, we also clarify some confusing terminology. We then propose a three-stage process that could lead to the establishment of methodological standards in social and economic simulations.

A lengthy and intensive debate about the role of sociology in agent based social simulation dominated the email list [email protected] during the autumn of 2000. The debate turned on the importance of models being devised to capture the properties of whole social systems and whether those properties should determine agent behaviour or, conversely, whether the properties of social systems should emerge from the behaviour and interaction of the agents and, if so, how that emergence should be represented. The positions of four of the main protagonists concerned specifically with the modelling issues are reprised and extended in this symposium.

In education contexts, agent-based simulations have been used at all levels, from the individual to the classroom to the state, to explore individual-level interactions and often to provide conclusions and explanations that could support decision-making.  The aim of this research was to develop an empirically-grounded classroom lessons behaviour model and explore the theoretical consequences of the model design and the modelling assumptions, to understand the mechanisms of lesson interactions and to assess whether the results and explanations were plausible and realistic.  The model was to be as realistic (not simplistic) as possible, addressing the limitations found in current lesson-related simulations and extending the use of agent-based simulations in classroom research to full-lessons with full-classes.
A typical empirically-driven agent-based modelling and simulation methodology was followed, incorporating an investigative case study at a UK secondary school.  A comprehensive agent-based model of classroom lessons was formulated and a lesson event recording tool was developed and used to record a wide range of student and teacher activities.  These data were used to calibrate and validate the simulation model.  Three agent types were incorporated:  students, teacher and teaching assistant.  Agent decision-making was modelled using conventional production rules (one set for each agent type) that integrated the influences from, in order of significance, the lesson plan (which specifies the desired behaviour and is enacted by the teacher), the current circumstances (who is doing what and where) and, for students only, their historical empirical activity state frequencies.
The simulation model was validated with the help of experienced teachers, who considered that it embodied plausible theories of classroom behaviours.  It was seen to generate plausible causal agent-level explanations for some important lesson dynamics and therefore judged to be a useful lesson analytics and decision-support tool, enabling educators to explore the consequences of a range of lesson interventions.

The topic of IT outsourcing has been around in academic research for the last fifteen years. Despite the lack of commonly accepted interpretation of outsourcing outcomes, the practice of outsourcing in modern corporations is proliferating. This trend forced both practitioners and academics to theorize and speculate on the underlying momentum towards outsourcing. Past research on IT outsourcing has mainly focused on the transaction itself, without investigating the strategic characteristics of the organization not to mention a built-in social framework of the firm or social context a firm is located in. This captures the widely held perception that organizational members make sourcing decisions based upon an economic rationale and regard social factors as negligible in their influence on the overall picture of outsourcing. This paper introduces a novel approach for investigation of various theories used to account for make-or-buy decisions. It goes down the line of Agent-Based Social...

In this paper we adapt Axelrod's metanorms model to run on arbitrary interaction structures. We propose a hybrid analytical methodology combining computer simulations with a novel mathematical approach that abstracts some details of evolutionary dynamics while retaining explicit and exact representation of underlying network topology. We construct simple network statistics based on the clustering coefficient and first order degree distribution of the interaction network as strong predictors of the emergence of cooperative ...

The interdependence and complexity of socio-technical systems and availability of a wide variety of policy measures to address policy problems make the process of policy formulation difficult. In order to formulate sustainable and efficient transport policies, development of new tools and techniques is necessary. One of the approaches gaining ground is policy packaging, which shifts focus from implementation of individual policy measures to implementation of combinations of measures with the aim of increasing efficiency and effectiveness of policy interventions by increasing synergies and reducing potential contradictions among policy measures. In this paper, we describe the development of a virtual environment for the exploration and analysis of different configurations of policy measures in order to build policy packages. By developing systematic approaches it is possible to examine more alternatives at a greater depth, decrease the time required for the overall analysis, provide real-time assessment and feedback on the effect of changes in the configurations, and ultimately form more effective policies. The results from this research demonstrate the usefulness of computational approaches in addressing the complexity inherent in the formulation of policy packages. This new approach has been applied to the formulation of policies to advance sustainable transportation.

Combined forces interventions in the UK's illegal drug market can be designed and evaluated using a serious game, where the illegal drug market can be simulated using an Agent-Based Model with a many different classes of human behaviour. This paper presents NARCSim the Intelligent-ABM that powered an illegal drug market serious game, created to investigate innovative methods for training people working to reduce the effect of drugs on the community. NARCSim is an Agent-Based Social Simulation of the behaviours of Heroin, Cannabis and Cocaine users, dealers, police and treatment officers in UK. The agents' behaviour were formalised using Xmachines and implemented on the agent-based framework FLAME.

The global effort toward sustainable development has initiated a transition in water management. Water utility companies use water-pricing policies as an instrument for controlling residential water demand. To support policy makers in their decisions, the authors have developed DAWN, a hybrid model for evaluating water-pricing policies. DAWN integrates an agent-based social model for the consumer with conventional econometric models and simulates the residential water demand-supply chain, enabling the evaluation of different scenarios for policy making. An agent community is assigned to behave as water consumers, while econometric and social models are incorporated into them for estimating water consumption. DAWN's main advantage is that it supports social interaction between consumers, through an influence diffusion mechanism, implemented via inter-agent communication. Parameters affecting water consumption and associated with consumers' social behavior can be simulated with DAWN. Real-world results of DAWN's application for the evaluation of five waterpricing policies in Thessaloniki, Greece, are presented.

A lengthy and intensive debate about the role of sociology in agent based social simulation dominated the email list [email protected] during the autumn of 2000. The debate turned on the importance of models being devised to capture the properties of whole social systems and whether those properties should determine agent behaviour or, conversely, whether the properties of social systems should emerge from the behaviour and interaction of the agents and, if so, how that emergence should be represented. The positions of four of the main protagonists concerned specifically with the modelling issues are reprised and extended in this symposium.

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.

In the carpooling, individuals need to communicate, negotiate and in most cases adapt their daily schedule to enable cooperation. Through negotiation, agents (individuals) can reach complex agreements in an iterative way which meet the criteria for successful negotiation. The result of the negotiation depends on “negotiation mechanism” used to match and on the behavior of the agents involved in the negotiation process. This paper presents an organizational and agent-based model for commuting by candidate carpoolers using a simple negotiation mechanism aimed at finding an acceptable agreement between agents to carpool. Initially, the agents involved in exploration process, search for their partners via some kind of Agent Communication Language (ACL); after finding potential partners, they start a negotiation to find matched partner to carpool. After having found a good match, the agents can carpool for a specified time period. The agents join the carpool group when the negotiation is...

using random-walk algorithms as the randomization approach in an attempt to reproduce human behaviors abound in the literature. However, almost all human actions are nonrandom and include a probabilistic component. This work investigates the use of a probabilistic distribution-based randomization method based on Lévy flight as an improvement to the use of traditional random-walk algorithms in cognitive agent models. The fact that Lévy flight has been shown to be a more suitable approach than random walk in mimicking natural phenomena, encouraged us to assess whether it could be a more robust randomization method in our agent-based social simulations. Experiments were carried out using Lévy flight as the randomization method in our new hybrid evolutionary agent model for ABSS, modeling a realistic scenario of the spread of dengue fever. Previous papers proved that this kind of agent models, which incorporates two components namely, genetic and cultural layers, produce good simulat...

Agent-based social simulations have been widely used to help social scientists on the understanding of several social phenomena. Traditional approaches to agents most often tackle well the behavioral and the temporal aspects of the carried out simulations. However, a frequent limitation in social simulations is the lack of simultaneous support for spatial specifications of social structures. That is, the incorporation

The basic presupposition of model replication activities for a computational model such as an agent-based model (ABM) is that, as a robust and reliable tool, it must be replicable in other computing settings. This assumption has recently gained attention in the community of artificial society and simulation due to the challenges of model verification and validation. Illustrating the replication of an ABM representing fraudulent behavior in a public service delivery system originally developed in the Java-based MASON toolkit for NetLogo by a different author, this paper exemplifies how model replication exercises provide unique opportunities for model verification and validation process. At the same time, it helps accumulate best practices and patterns of model replication and contributes to the agenda of developing a standard methodological protocol for agent-based social simulation.

This paper presents J-MADeM, a new market-based multi-agent ap- proach devoted to perform social simulations with BDI agents. J-MADeM is avail- able as an open-source library integrated into Jason (2), the successful interpreter for the AgentSpeak programming language (16). The aim of this work is to improve Jason by incorporating the main features of MADeM (10), a market-based mech- anism

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 c...

Serious games are designed to train and educate learners, opening up new learning approaches like exploratory learning and situated cognition. Despite growing interest in these games, their design is still an artisan process. On the basis of experience in designing computer simulation, this paper proposes an agent-based approach to guide the design process of a serious game. The proposed methodology allows the designer to bring forward the assessment of educational effectiveness to the design phase and to strike the right equilibrium between educational effectiveness and entertainment, realism and complexity. To this end, an agent based approach is proposed because it provides the actors involved in designing the game with specific tools and guidelines for determining whether the proposed model is clear and comprehensible to the students. The design of the PNPVillage game is used as a case study. The PNPVillage game aims to introduce and foster an entrepreneurial mindset among young...

Description A computer assisted technique for knowledge elicitation assists in building rules of how people respond to a variety of stimuli and scenarios of environmental and social conditions. Agent based social simulation is a relatively formal approach to stakeholder and institutional analysis. It is a computer programming method that uses software agents to represent the positions, boundaries, and actions of stakeholders. This approach is one of the few means to realistically simulate the behavior of stakeholder networks in the context of the rules, norms, and shared strategies from social and economic institutions. This approach can be applied at various stages of an assessment. One example is that agent based social simulation can incorporate socioeconomic scenarios that are constructed as sets of rules regarding, for example, environmental values, regulation, and economic goals. An advantage of this approach is that the realization of socioeconomic scenarios is the outcome of stakeholder behavior rather than being exogenously imposed in a way that bears little relation to actual decision making processes. Appropriate Use Applicable to various stages of the design of a strategy to respond to climate change and its subsequent implementation in specific measures. Scope Global, but most appropriate at national or local level. Key Output Insight into how the decision making and implementation processes. For example, realistic socioeconomic pathways constructed as the outcome of multiple decisions. Key Input A mixture of qualitative and quantitative data. Ease of Use Varies, though constructing an agent based social simulation model would require significant expertise. Training Required Some training is useful, but expertise in policy analysis is more important than specific analytical techniques when it comes to using and interpreting results of agent based social simulation. Training Available Very little experience has been gained regarding these approaches to date, and hence no formal training or certification is available. However, occasional workshops are offered. See documentation section below. Computer Requirements Personal computer. Documentation Center for Policy Modeling at Manchester Metropolitan University is one of the world leaders in agent based social simulation. The CPM developed a user friendly software package (SDML) to facilitate model development. http://cfpm.org/ and http://firma.cfpm.org/. Applications Agent based social simulation is only beginning to be applied to climate change. Oxford University's Environmental Change Unit is collaborating with the CPM on various applications to integrated assessment of climate policy. Also, the Carnegie Mellon global change program has elements of agent behavior in the Integrated Climate Assessment Model. A European Union project on integrated water resource management (Freshwater Integrated Resource Management Agents, coordinated by the University of Surrey) will develop agent based approaches further.

This article compares three agent-based social simulation models in the area of land use change using a model documentation protocol, ODD, from the ecological literature, with a view to examining how well it enables the models to be compared, how well fitted it is to social simulations, and how successful it might be in increasing communication between individual-and agent-based modellers. Such shared protocols can facilitate model review, comparison, and ultimately, replication. We initially conclude that the framework holds promise as a standard communication mechanism, although some refinements may be needed.

In this paper we adapt Axelrod's metanorms model to run on arbitrary interaction structures. We propose a hybrid analytical methodology combining computer simulations with a novel mathematical approach that abstracts some details of evolutionary dynamics while retaining explicit and exact representation of underlying network topology. We construct simple network statistics based on the clustering coefficient and first order degree distribution of the interaction network as strong predictors of the emergence of cooperative ...

The “Keep It Simple, Stupid” principle is a recommended rule for modelling complex phenomena. However, there must be a compromise between simplification and expressiveness, determined by the results produced by the model. Here we propose to gradually increase the complexity of a model, so we can improve its behaviour. This incremental “deepening” process is an attempt to approach the real phenomena, so resulting in a better model, provided that an accurate analysis reveals the right steps. As application we propose an agent-based data-driven model of the evolution of moral values in the Spanish post-modern society. We focus on improving the demographic mechanisms so that the system output follows the evolution of Spanish population. In order to do that, we raise the amount of quantitative input information of the system, improve its statistical distributions, and change the time of evolution, together with other commented changes.

©Copyright JASSS JASSS logo. Shah Jamal Alam, Ruth Meyer, Gina Ziervogel and Scott Moss (2007). The Impact of HIV/AIDS in the Context of Socioeconomic Stressors: an Evidence-Driven Approach. Journal of Artificial Societies and Social Simulation vol. 10, no. ...

In this work we try to draw an interdisciplinary framework aimed to integrate a socio-cognitive approach with organizational research about industrial clusters, in order to investigate whether and how social evaluations may affect clusters' dynamics. Industrial districts are sort of ���small-worlds��� that provide a suitable environment for testing the predictions of our model through multi-agent-based social simulation (MABSS) experiments. Artificial agents will be allowed to exchange products and to transmit social evaluations, ...

The classical theory of computation is not an adequate model of reality for agent-based simulation in the social sciences. The paradigm of intentional computation seems to be the only one possible to reflect the multiparadigmatic character of social science in terms of agent-based computational social science. This is a paradigm that enlarges the concept of valid computation, which must be dependent on the particular theoreticalmethodological context of the social scientist.

1 Department of Information Science and Technology, ISCTE/DCTI, Lisbon, Portugal [email protected] http://www.iscte.pt/~nmcd 2 Intelligent Techniques Laboratory, University of São Paulo, Brazil [email protected] http://www.pcs.usp.br/~jaime 3 Department of ...

Abstract. The topic of IT outsourcing has been around in academic research for the last fifteen years. Despite the lack of commonly accepted interpretation of outsourcing outcomes, the practice of outsourcing in modern corporations is proliferating. This trend forced both practitioners and academics to theorize and speculate on the underlying momentum towards outsourcing. Past research on IT outsourcing has mainly focused on the transaction itself, without investigating the strategic characteristics of the organization not to mention a built-in social framework of the firm or social context a firm is located in. This captures the widely held perception that organizational members make sourcing decisions based upon an economic rationale and regard social factors as negligible in their influence on the overall picture of outsourcing. This paper introduces a novel approach for investigation of various theories used to account for make-or-buy decisions. It goes down the line of Agent-Ba...

The use of Agent-Based Social Simulations (ABSS) using random-walk algorithms as the randomization approach in an attempt to reproduce human behaviors abound in the literature. However, almost all human actions are nonrandom and include a probabilistic component. This work investigates the use of a probabilistic distribution-based randomization method based on Lévy flight as an improvement to the use of traditional random-walk algorithms in cognitive agent models. The fact that Lévy flight has been shown to be a more suitable approach than random walk in mimicking natural phenomena, encouraged us to assess whether it could be a more robust randomization method in our agent-based social simulations. Experiments were carried out using Lévy flight as the randomization method in our new hybrid evolutionary agent model for ABSS, modeling a realistic scenario of the spread of dengue fever. Previous papers proved that this kind of agent models, which incorporates two components namely, genetic and cultural layers, produce good simulations results. The aim here is to assess whether there is qualitative and quantitative predictive power of the model. This paper looks at the following decision components variations together with the new randomization method: (i) agents only with genetic component; (ii) agents only with cultural component; and (iii) agents with both genetic and cultural components. The results show the beneficial impact in Lévy flight that leads to better prediction in all combinations of decision components.

©Copyright JASSS JASSS logo. Shah Jamal Alam, Ruth Meyer, Gina Ziervogel and Scott Moss (2007). The Impact of HIV/AIDS in the Context of Socioeconomic Stressors: an Evidence-Driven Approach. Journal of Artificial Societies and Social Simulation vol. 10, no. ...

Modelling the evolution of moral values in a society is a complex problem that involves many interwined aspects. The approach presented in this paper takes information from a common tool of sociologists, public surveys, as input to build the model by following a data-driven approach, to analyse and interpret the impact of each factor separately, and their mutual influence. The system handles thousands of heterogeneous agents, with their own life cycle, reproduction patterns and complex social relationship dynamics including friendship. The emergence of a robust social network was a consequence of the system set up. Its output is consistent with respect to the ideological, religious and demographic parameters observed in real world surveys.

In this paper we compare models of two different kinds of processes in multi-agentbased social simulations (MABSS): military conflict within a states-system (GeoSim), and land use and ownership change (FEARLUS). This is a kind of model-to-model comparison which is novel within Multi-Agent Based Simulation research, although well-known within mathematics, physics and biology: comparing objects (in this case MABSS) drawn from distinct research domains, in order to draw out their structural similarities and differences. This can facilitate research in both domains, by allowing the use of findings from each to illuminate the other. Based on the similarities between FEARLUS and GeoSim, we conclude by identifying a new class of MABSS models based on territorial resource allocation processes occurring on a 2-dimensional space (which we define as the "TRAP 2 " class). The existence of the cross-domain TRAP 2 class of models in turn suggests that MABSS researchers should look for other members of the class, sharing some of the properties or dynamics common to the GeoSim and FEARLUS models compared in this study: a systematic comparison of a set of related models from a range of apparently distinct domains should generate insights into both MABSS modeling, and the domains concerned.

Modern knowledge-intensive economies are complex social systems where intertwining factors are responsible for the shaping of emerging industries: the self-organising interaction patterns and strategies of the individual actors (an agency-oriented pattern) and the institutional frameworks of different innovation systems (a structureoriented pattern). In this paper, we examine the relative primacy of the two patterns in the development of innovation networks, and find that both are important. In order to investigate the relative significance of strategic decision making by innovation network actors and the roles played by national institutional settings, we use an agent-based model of knowledge-intensive innovation networks, SKIN. We experiment with the simulation of different actor strategies and different access conditions to capital in order to study the resulting effects on innovation performance and size of the industry. Our analysis suggests that actors are able to compensate for structural limitations through strategic collaborations. The implications for public policy are outlined.

School of Publ i c Pol i cy U ni versi t y of Bi rm i ngham U ni t ed K i ngdom A bstract Represent at i on and i nt erpret at i on of si mul at i on sem ant i c cont ent i s a chal l engi ng probl em at t he heart of i ssues such as si mul at i on com posabi l i t y and sym bi ot i c si mul at i on. Thi s paper i nt roduces an aut om at ed approach t o dynam i c onl i ne i nt erpret at i on of si mul at i ons usi ng AI t echni ques. The approach i s descri bed i n t he cont ext of agent -based soci al si m ul at i ons.

Agent-based models, perhaps more than other models, feature large numbers of parameters and potentially generate vast quantities of results data. This paper shows through the FEARLUS-G project (an ESRC e-Social Science Initiative Pilot Demonstrator Project) how deploying an agent-based model on the Semantic Grid facilitates international collaboration on investigations using such a model, and contributes to establishing rigorous working practices with agent-based models as part of good science in social simulation. The experimental workflow is described explicitly using an ontology, and a Semantic Grid service with a web interface implements the workflow. Users are able to compare their parameter settings and results, and relate their work with the model to wider scientific debate.

Agent-based social simulation (ABSS) as a main computational approach to social simulation has attracted increasing attention in the field of social computing. With the development of computer and information technologies, many new ABSS approaches have been proposed with wide application.. In this paper, we aim at reviewing research and applications of agent-based social simulation and modeling in recent years from a social computing perspective. We identify the underlying social theories for ABSS, its simulation and modeling techniques, and computational frameworks from both individual agent and multi-agent system perspective. We finally address some future research issues in agent-based social simulation and modeling.