Social Practices: a Complete Formalization
This work addresses the need for improved modeling approaches in multi-agent systems to handle interdependencies among heterogeneous parties, though it appears incremental as it builds on existing concepts like conventions and norms.
The paper tackles the challenge of modeling complex social interactions in multi-agent systems by formalizing a social framework based on Social Practices, which specify expected behaviors in social contexts to aid agent reasoning and planning.
Multi-agent models are a suitable starting point to model complex social interactions. However, as the complexity of the systems increase, we argue that novel modeling approaches are needed that can deal with inter-dependencies at different levels of society, where many heterogeneous parties (software agents, robots, humans) are interacting and reacting to each other. In this paper, we present a formalization of a social framework for agents based on the concept of Social Practices as high level specifications of normal (expected) behavior in a given social context. We argue that social practices facilitate the practical reasoning of agents in standard social interactions. Thus they can support deliberations for complex situations just like conventions and norms. However, they also come with a social context that gives handles for social planning and deliberation in top of the normal functional deliberation. The main goal of this paper is to give a formalization of social practices that can be used as a basis for implementations and defining precise structures within which social learning can take place.