When "I" Becomes "We": Modelling Dynamic Identity on Autonomous Agents

Individuals change who they are in response to their social environment. In other words, one's identity is dynamic, varying according to context (e.g., individuals present, place, task). Identity has a significant impact on an individual's behaviour. Researchers have been interested in understanding how contextual aspects shape identity and, in turn, how identity influences behaviour. Agent-based simulation models are great tools to identify and predict behaviour associated with these identity processes. In addition, agents can employ identity-related mechanisms based on social theories to become more socially believable and similar to humans. The Social Identity Approach (SIA) is one of the most influential theories covering social aspects of one's identity, with many of its concepts being applied in social simulation research. This paper formalizes the Dynamic Identity Model for Agents (DIMA), an existing agent-based model based on SIA, providing a detailed theoretical foundation of the model, as well as an overview of its integration as a component into a social agent architecture. In DIMA, agents perceive themselves either as distinct individuals (personal identity) or as members of a social group (social identity), acting according to their context-dependent active identity. Two simulation scenarios are presented here to illustrate the use of this model, one based on the Dictator Game and the other on a trash collection task. This work aims to guide other researchers who want to enhance their agents with the DIMA's identity salience mechanism. As a result, they would not only be able to assess how this mechanism influences behaviour based on the context, but they would also be able to explore the dynamics between personal and social identities.