Computer simulation has proved useful for modelling phenomena of traditionally social scientific interest, such as cooperation, coordination, organizational behavior, social dynamics, group and coalition formation, and the evolution of conventions and norms. Multi-agent researchers soon came to realize how crucial these topics are within their field. In particular, the study of emergence of social phenomena such as organizational performance and optimization, cultural norms, institutional forms has become a major direction of research in MAS. In turn, such social modelling rings into play a variety of normative concepts, such as conventions and obligations, and phenomena, such as commitment and responsibility, and draws attention to how these phenomena evolve among computational agents in interaction. These concerns have led social simulators to pay increasing attention to agent modelling. Dissatisfied with the model of the rational social actor, they have developed simulation models of evolutionary social phenomena incorporating representations of cognition derived other disciplines such as cognitive science and social psychology. However, the model of the agent used is essentially behavioural and frrequently more rudimentary than those developed in some areas of AI.
The computational study of social organizations and institutions is a topic of growing interest in both the computer science and social science communities. In the formal/computational scientific communities, logical philosophy and social philosophy have a long tradition in studying institutions and obligations. Interest in such issues is rapidly growing. This is shown by several indicators, including (a) the number of workshops, etc.; (b) the diffusion of notions of obligation, convention, trust, commitment, reciprocity, right, permission, etc. in the research on intelligent agents; (c) the attention paid to norm-based phenomena in designing and implementing situated intelligent agents (consider the trade-off between robust performances and flexibility: formal and computational research on commitment essentially proceeds from the question of how to design intelligent, adaptive, flexible agents that exhibit robust performances; moreover, think of the research on conventions as solutions to problems of coordination among autonomously interacting agents). Interestingly, the more the MAS researchers pay attention to evolutionary and dynamic organizations and institutions, the more they use computer simulation (for example, simulation-based studies on the evolution of conventions, commitment, altruism, in MAS, and the role of simulation in the study of organizations). Where the social sciences meet the physical and biological aciences as, for example, in the modelling of climate change, there is growing disenchantment with analytic equilibrium approaches to analysis of social and economic systems. Agent-based simulation methods are proving attractive to physical scientists seeking to take socioeconomic factors into account in the analysis of such issues. Increasingly, we are seeing agent-based social simulation used to provide more realistic alternatives to analyses of the whole area of exchange with particular success in generating empirically more satisfactory models of financial markets. Within the AgentLink framework, these various communities are given the opportunity to meet and discuss matters related to the theme proposed. The theme is transverse to several pure and applied research fields:
- electronic commerce, trading relationships intelligent information agentsroboticsorganizational structure and changeauthorizationdelegationsocial and collective actioncommitmentreciprocity and cooperationinstitutions, empowerment, and rolescoordination and conventions
- autonomous social agents modelling
An issue exercising the social simulation community is that of emergence which has important implications for all of the above areas.