From artificial societies to new social science theory

Abstract. We identify two distinct themes in social science modelling. One, more specific, approach is that of social simulation which addresses how behaviour of many actors can lead to emergent effects. We argue that this approach, while useful as a tool in social science policy development, is fundamentally constrained due to the fact that its models are developed within the society they are supposed to model. Alternatively, the second theme looks to take a more holistic view by taking inspiration from systems sociology. This approach looks to build societies from the bottom up and may allow us to generate new perspectives in social theory.

Inteligência Artificial, Tecnologias Informacionais E Seus Possíveis Impactos Sobre As Ciências Sociais

[No abstract available]sv/55879Bainbridge, W.S., Artificial Social Intelligence (1983) Annual Review of Sociology, 20, pp. 407-436Bainbridge, W.S., Cyberspace: Sociology's Natural Domain (1999) Contemporary-sociology, 28 (6), pp. 664-667. , novBaldi, S., Normative versus Social Constructivist Processes in the Allocation of Citations: A network-analytic model (1998) American Sociological Review, 63, pp. 829-846Banerjee, S., Reproduction of Social Structures: An artifical intelligence model (1986) Journal of Conflict Resolution., 30, pp. 221-252Boden, M.A., Artificial Intelligence and Social Forecasting (1984) Journal of Mathematical_Sociology, 9 (4), pp. 341-356Brent, E.E., Erving: A program to teach sociological reasoning from the dramaturgical perspective (1989) Teaching Sociology, 17, pp. 38-48Brent, E., Thompson, A., Vale, W., Sociology: A computacional approach to sociological explanations (2000) Social Science Computer Review, 18, pp. 223-235Brin, D., The Transparent Society (1996) Wired, 4 (12), pp. 260-262Caplow, T., (1968) Two Against One: Coalitions in Triads, , Englewood Cliffs, Prentice-HallChablo, A., What Can Artificial Intelligence Do for Anthropology? (1996) Current Anthropology, 37, pp. 553-555Collins, R., (1992) Sociological Insight: An Introduction to Non-obvious Sociology. 2. Ed., pp. 155-184. , New York, Oxford University Press, Can Sociology Create an Artificial IntelligenceDreyfus, H.L., Dreyfus, S.E., (1986) Mind over Machine: The Power of Human Intuition_Expertise in the Era of the Computer, , New York, Free PressEncyclopedia Britannica. 2001. Artificial Intelligence. Herbert A.Simon (www.britannica.com)Epstein, J.M., Axtell, R., (1996) Growing Artificial Societies: Social Sceince from the Bottom Up, , http://www.brook.edu/sugarscape/links.htm, Washington, DC, Brookings Institute. Disponível na internetEvans, W., Teaching Computers to Watch Television: Content-based image retreival for content analysis (2000) Social Science Computer Review, 18, pp. 246-257Fan, D.F., Computer Content Analysis of press Coverage and Prediciton of Public Opinion for the 1995 Sovereignty Referendum in Quebec (1997) Social Science Computer_Review, 15, pp. 351-366FEATHERMAN, D. conversa particular com David Featherman, Diretor do Institute for Survey Research da University of Michigan em Belo Horizonte, 19 junho . 2000Glaser, B., Strauss, A., (1967) The Discovery of Grounded Theory, , Chicago, Aldine PublishingGilbert, G.N., Heath, C., (1985) Social Action and Artificial Intelligence: Surrey Conferences on Sociological Theory and Method 3, , Aldershot, Gower PublishingGoldspink, C., Modelling Social Systems as Complex: Towards a social simulation meta-model (2000) Journal of Artificial Societies and Social Simulation, 3 (2). , www.soc.surrey.ac.uk/JASSS/3/2/1.html, Disponível na internetJohnston, J., Walton, C., Reducing response effects for sensitive questions: A computer-assisted self interview with audio (1995) Social Science Computer Review, 13, pp. 304-319Kimber, R., Artificial Intelligence and the Study of Democracy (1991) Social Science Computer Review, 9, pp. 381-398Lavoratti, L., Choque de transparência vai incluir Internet (2000) Estado de São Paulo, , 17 de agosto, A 4Lessler, J.T., Developing Computer Assisted Interviewing (CAI) for the National Household Survey on Drug Abuse (2000) Journal of Drug Issues, 30, pp. 9-34Mangabeira, W., CAQDAS and its Diffusion Across four Countries: National Specificities and Common Themes (1996) Current Sociology, 44 (3), pp. 191-205Murdoch, G.P., (1949) Social Structure, , New York, MacmillanPort, O., The Mind is Immortal (1999) Business Week, pp. 52-53. , August 30(1998) Simulating Organizations: Computational Models of Institutions and Groups, , PRIETULA, M.J., CARLEY, K.M. e GASSER, L. (orgs) . Menlo Park, AAAI Press e MIT PressRaudensbush, S.W., Sampson, R.J., Ecometrics: Toward a science of assessing ecological settings, with application to the systematic social observation of neighbourhoods (1997) 'American Society of Criminology', , Paper apresentado as encontro annual da San DiegoReiss, A.J., Systematic Observations of Natural Social Phenomena (1971) Sociological Methodology, pp. 3-33. , COSTNER, H. (org.) San Francisco, Jossey-BassRyssevik, J., Laboratories for Comparative Social Science (1994) International Social Science Journal., (142), pp. 587-596(2000) Seminário Survey Metropolitano de Belo Horizonte, , Belo Horizonte, FAFICH/UFMG. 19-21 de junhoTurkle, S., (1996) Life on the Screen: Identity in the Age of the Internet, , London, Weidenfeld & Nicholso

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

The Ribbon of Love: Fuzzy-Ruled Agents in Artificial Societies

The paper brings two motivations to the theoretical explorations of social analysis. The first is to enrich the agent based computational sociology by incorporating the fuzzy set theory in to the computational modeling. This is conducted by showing the importance to include the fuzziness into artificial agent’s considerations and her way acquiring and articulate information. This is continued with the second motives to bring the Darwinian sexual selection theory – as it has been developed broadly in evolutionary psychology – into the analysis of social system including cultural analysis and other broad aspects of sociological fields. The two was combined in one computational model construction showing the fuzziness of mating choice, and how to have computational tools to explain broad fields of social realms. The paper ends with some opened further computer program development

Agent-based models and individualism: is the world agent-based?

Agent-based models (ABMs) are an increasingly popular tool in the social sciences. This trend seems likely to continue, so that they will become widely used in geography and in urban and regional planning. We present an overview of examples of these models in the life sciences, economics, planning, sociology, and archaeology. We conclude that ABMs strongly tend towards an individualist view of the social world. This point is reinforced by closer consideration of particular examples. This discussion pays attention to the inadequacy of an individualist model of society with reference to debates in social theory. We argue that because models are closed representations of an open world it is important that institutions and other social structures be explicitly included, or that their omission be explained. A tentative explanation for the bias of ABMs is offered, based on an examination of early research in artificial intelligence and distributed artificial intelligence from which disciplines the approach is derived. Some implications of these findings are discussed. We indicate some useful research directions which are beginning to tackle the individualism issue directly. We further note that the underlying assumptions of ABMs are often hidden in the implementation details. We conclude that such models must be subject to critical examination of their assumptions, and that model builders should engage with social theory if the approach is to realise its full potential

The Role Of Technology and Innovation In The Framework Of The Information Society

The literature on the information society indicates that it is a still-developing field of research. It can be explained by the lack of consensus on basic definitions and research methods. There are also different judgments on the importance and the significance of the information society. Some social scientists write about a change of era, others emphasize parallelism with the past. There are some authors who expect that the information society will solve the problems of social inequalities, poverty and unemployment, while others blame it on the widening social gap between the information haves and have-nots. Various models of the information society have been developed so far and they are so different from country to country that it would be rather unwise to look for a single, all-encompassing definition. In our time a number of profound socio-economic changes are underway. Almost every field of our life is affected by the different phenomena of globalization, beside the growing role of the individual; another important characteristic of this process is the development of an organizing principle based on the free creation, distribution, access and use of knowledge and information. The 1990s and the 21st century is undoubtedly characterized by the world of the information society (as a form of the post-industrial society), which represents a different quality compared to the previous ones. The application of these theories and schools on ICT is problematic in many respects. First, as we stated above, there is not a single, widely used paradigm which has synthesized the various schools and theories dealing with technology and society. Second, these fragmented approaches do not have a fully-fledged mode of application to the relationship of ICT and (information) society. Third, SCOT, ANT, the evolutionary- or the systems approach to the history of technology – when dealing with information society – does not take into account the results of approaches (such as information science or information systems literature or social informatics, information management and knowledge management, communication and media studies) studying the very essence of the information age: information, communication and knowledge. The list of unnoticed or partially incorporated sciences, which focuses on the role of ICT in human information processing and other cognitive activities, is much longer

The Explanatory Potential of Artificial Societies

It is often claimed that artificial society simulations contribute to the explanation of social phenomena. At the hand of a particular example, this paper argues that artificial societies often cannot provide full explanations, because their models are not or cannot be validated. Instead, artificial societies may sometimes provide potential explanations. It is shown that these potential explanations, if they contribute to our understanding, considerably differ from the standard kind of potential causal explanations. Instead of possible causal histories, simulations offer possible functional analyses of the explanandum. The paper discusses how these two kinds of potential explanations differ, and how possible functional analyses can be appraised

EMERGING THE EMERGENCE SOCIOLOGY: The Philosophical Framework of Agent-Based Social Studies

The structuration theory originally provided by Anthony Giddens and the advance improvement of the theory has been trying to solve the dilemma came up in the epistemological aspects of the social sciences and humanity. Social scientists apparently have to choose whether they are too sociological or too psychological. Nonetheless, in the works of the classical sociologist, Emile Durkheim, this thing has been stated long time ago. The usage of some models to construct the bottom-up theories has followed the vast of computational technology. This model is well known as the agent based modeling. This paper is giving a philosophical perspective of the agent-based social sciences, as the sociology to cope the emergent factors coming up in the sociological analysis. The framework is made by using the artificial neural network model to show how the emergent phenomena came from the complex system. Understanding the society has self-organizing (autopoietic) properties, the Kohonen’s self-organizing map is used in the paper. By the simulation examples, it can be seen obviously that the emergent phenomena in social system are seen by the sociologist apart from the qualitative framework on the atomistic sociology. In the end of the paper, it is clear that the emergence sociology is needed for sharpening the sociological analysis in the emergence sociology