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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.

Norms influence behaviour in many ways. In situations such as the COVID-19 pandemic where the effect of policies on the spread of the virus is evaluated, this leads to disputes about their effectiveness. In order to build agent-based social simulations that give proper support for this evaluation process we need agents that properly deal with norms. In this paper we present a new agent deliberation architecture that takes more aspects of norms into account than traditional architectures have done. Dealing properly with norms means that agents can reason through the consequences of the norms, that they are used to motivate and not just constrain behaviour, and that the agents can violate the norm as well. For the former we use the ideas of perspectives on norms, while the latter is enabled through the use of values. Within our architecture we can also represent habitual behaviour, context sensitive planning, and through the use of landmarks, reactive planning. We use the example of a restaurant-size based restriction to show how our architecture works.

Norms are a crucial part of human behavior that received a lot of attention within the social simulation community. However, some aspects—up until now—have not been addressed in existing agent architectures, such as their motivational aspects and their importance and impact in planning and action selection. In this paper we present an agent architecture capable of grasping this potential of norms. We use perspectives to reflect how different people engage with a norm, and how it effects their long-term goals, their planning, and course of action. Our architecture is capable of having fast habitual-like behavior, as well as more complex deliberation if necessary.

Social simulations can be a powerful tool for policy makers and other decision makers to support them in their decision making process. To be a powerful tool, it is not only important that the agents in the simulation exhibit realistic–human like—behavior, but also that the simulation is empowering the policy maker to use it in a—for them—meaningful way. To tackle this problem, we require interaction tools and visualization capabilities necessary to support non-expert users (such as policy makers). To understand what these non-expert users need, we performed a focus group study to gain insights into the potential requirements of such an interaction tool with respect to norms. This resulted in a list of requirements to support non-expert users in the analysis of norm conflicts after they happened during the simulation. But more importantly we are calling for a new research agenda in the field of social simulation to support non-expert users with the abstract analysis of norms before conflicts happen in the simulation run, as the results showed that the participants were not able to do that kind of analysis.