The Dynamic Nature of Goals and Message Production as Revealed in a Sequential Analysis of Conflict Interactions

Although message‐production theories often assume that goals behave dynamically to direct communication behavior, few studies consider the interconnectedness of goals and behavior throughout interactions. Here, the interrelationship of communication goals and tactics was examined through a sequential analysis of 47 conflict interactions between close friends or dating partners. It was posited that for both the initiators and resistors in a conflict, the importance of relational or other‐identity goals would be associated with the use of integrative tactics and the importance of instrumental or self‐identity goals would be related to the use of distributive tactics. We examined these predictions within and across partners. Analyses indicated that for both conflict initiators and resistors, the importance of a combination self/instrumental goal predicted the use of distributive tactics and the importance of an other‐identity goal lead to partner‐oriented tactics. For resistors, the importance of an instrumental goal was associated with the use of distributive tactics and the importance of a combination identity/relational goal was aligned with issue‐oriented tactics as well. Across partners, several significant patterns between one partner’s use of distributive or integrative tactics and the other partner’s goals were observed. Implications of the results for understanding conflict and message production are discussed.     

On working through: a model from artificial intelligence

Working through is centrally important to clinical psychoanalysis. It is inadequately explained in analytic theory. An artificial intelligence model of the process is proposed. Models of problem solving show that the complexity of necessary computation is an important determinant of how a problem is solved. Not optimal, but only good enough solutions are usually found. The quality of solutions depends on the time and resources available. Generally it is far easier to use existing methods than to develop new approaches. When problems must be solved in an emergency fashion, as in trauma, poor solutions are likely to emerge. In studying the annealing of metals and other complex optimization problems, a process, the Boltzman algorithm, was discovered, which continues the search for better solutions while gradually developing a coherent structure of the overall solution. The algorithm provides a model both for psychoanalytic working through and for the normally ongoing process of psychological development and reworking whose deficiency is characteristic of much psychopathology. Working through in the analytic situation is the reactivation of this normal process, and a good analytic outcome is achieved when the process can continue without the analyst. Properties of the Boltzman algorithm clarify such concepts as "optimal" frustration and anxiety which correspond to working in the area where the stable but not rigid structures emerge in the algorithms operation. These studies are an example of how computer science and artificial intelligence are a potentially rich source for psychoanalytic theory.