Psychology defines personality as the stable traits of an individual, and cognitive research suggests that a set of core beliefs is at the root of these traits. From this perspective, two major questions remain unanswered: (1) What are the core beliefs that make up personality? (2) How are they acquired? An interesting answer is provided by attachment theory, according to which attachment is at the basis of personality. The current theoretical formulation, however, does not sufficiently clarify the relationship between the two. Adopting a cognitive-clinical approach, we put forward a novel version of attachment theory, arguing that it can better account for the relationship between attachment and personality, thereby providing more convincing answers to questions (1) and (2). In particular, we propose that: (A) attachment information is acquired over seven dimensions; (B) the acquisition of each dimension is induced by a specific caregiving feature and (C) realized through a specific acquisition mechanism – imprinting. In a nutshell, we propose an Attachment-Personality Model (APM) according to which seven attachment dimensions constitute the knowledge core of personality. We finally discuss the significant implications of the model, especially its clinical application in terms of conception, assessment, and treatment of mental disorders. The model can be empirically tested, and we suggest three ways to do that.

Attachment is an emotional bond between two people where one seeks care from the other. In the prototypical case, the child attaches to their mother. The most recent theoretical developments point out that attachment is multidimensional – meaning that the phenomenon pertains to multiple domains related to the relationship with the caregiver. However, researchers have so far modeled attachment computationally by mostly adopting a classical categorical (as opposed to dimensional) standpoint that sees the system as controlling caregiver proximity. In contrast, we adopt here a dimensional perspective (DP) and consider dimensions to be the system’s set-goals. We hypothesize that the resulting multidimensional controller should lead to valid (or even better) models of the phenomenon. To start testing this hypothesis, we built a DP-informed agent-based model of attachment inspired by the widely-studied Strange Situation Procedure. In this context, child and mother show the nature of attachment bonds through their behavioral and emotional expressions. By modeling them as point-agents moving in a two-dimensional arena, we simulated child-mother interactions for the avoidant and ambivalent attachment dimensions. The generated dynamical patterns – characterized by the alternation between approach and exploration – matched those described in the attachment literature, thereby confirming the implementability and validity of the DP.