Abstract
The purpose of the research programme detailed in this paper is to update the attachment control system framework that John Bowlby set out in his formulation of Attachment Theory. It does this by reconceptualising it as a cognitive architecture that can operate within multi-agent simulations. This is relevant to computational psychiatry because attachment phenomena are broad in scope and range from healthy everyday interactions to psychopathology. The process of attachment modelling involves three stages and this paper makes contributions in each of these stages. Firstly, a survey of attachment research is presented which focuses on two important attachment behavioural measures: the Strange Situation Procedure and the Adult Attachment Interview (AAI). These studies are reviewed to draw out key behavioural patterns and dependencies. Secondly, the empirical observations that are to be explained in this research programme are abstracted into scenarios which capture key behavioural elements. The value of behavioural scenarios is that they can guide the simulation design process and help evaluate simulations which are produced. Thirdly, whilst the implementation of these scenarios is still a work in progress, several designs are described that have been created and implemented as simulations. These include normative and non-pathological infant behaviour patterns observed across the first year of life in naturalistic observations and ‘Strange Situation’ studies. Future work is described which includes simulating dysfunctional infant behaviour patterns and a range of adult attachment behaviour patterns observed in the Adult Attachment Interview. In conclusion, this modelling approach is distinguished from other approaches in computational psychiatry because of the psychologically high level at which it models phenomena of interest.
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Petters, D., Beaudoin, L. (2017). Attachment Modelling: From Observations to Scenarios to Designs. In: Érdi, P., Sen Bhattacharya, B., Cochran, A. (eds) Computational Neurology and Psychiatry. Springer Series in Bio-/Neuroinformatics, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-49959-8_9
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