How consciousness modifies the motivation of belonging in agents

The motivation to belong and the capacity for social consciousness are key elements of human cognition. This paper presents a computational model that enables an artificial agent to assess its sense of belonging to a group and update this belief based on social feedback. The model is based on three central ideas: firstly, belief updates depend on the detection of inconsistencies between internal assumptions and external feedback; secondly, consciousness of such inconsistencies only arises when an evidence threshold is exceeded; and thirdly, the credibility of the feedback depends on source reputation. Drawing on theories of mind and false belief, as well as theories of consciousness, social cognition, and motivation, the model provides a functional framework through which to model the process by which agents become aware of their inclusion. The proposed computational model is validated through a case study, implemented and described using the ODD+D protocol, in which agents revise their beliefs about group inclusion through social interaction. The results demonstrate how consciousness, feedback, and social reasoning can be combined to produce behavior that is more akin to that of humans in artificial systems.