Abstract
For agent-based social simulations to be a powerful tool for policy makers and other decision makers in a given context (e.g. the current COVID-19 pandemic), they need to be socially realistic and thus, appropriately represent complex social concepts, such as social rules. In this paper, we focus on norms. Norms describe ‘normal’ behavior and aim at assuring the interests and values of groups or the society as a whole. People react differently to norms, and focus only on the parts that are relevant for them. Furthermore, norms are not only restrictions on behavior, but also trigger new behavior. Seeing a norm only as a restriction on certain behavior misses important aspects and leads to simulations that can be very misleading. Different perspectives need to be incorporated into the simulation to capture the variety of ways different stakeholders react to a norm and how this affects their interaction. We therefore present an approach to include these different perspectives on norms, and their consequences for different people and groups in decision support simulations. A perspective is specified by their goals, actions, effects of those actions, priorities in values, and social affordances. Through modeling perspectives we enable policy makers and other decision makers (the users) to be active in the modeling process and to tailor the simulation to their specific needs, by representing norms as modifiable objects, and providing textual and graphical representations of norms. This provides them with differentiated insights meaningful for the decisions they are faced with. We indicate the requirements for both the simulation platform as well as the agents that follow from our approach. Early explorations of our social simulation are showing the necessity of our approach.
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Kammler, C., Dignum, F., Wijermans, N., Lindgren, H. (2022). Changing Perspectives: Adaptable Interpretations of Norms for Agents. In: Van Dam, K.H., Verstaevel, N. (eds) Multi-Agent-Based Simulation XXII. MABS 2021. Lecture Notes in Computer Science(), vol 13128. Springer, Cham. https://doi.org/10.1007/978-3-030-94548-0_11
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