Good Theories in Need of Better Data: Combining Clinical and Social Psychological Approaches to Study the Mechanisms Linking Relationships and Health

The study of intimate relationships and health is a fast-growing discipline with numerous well-developed theories, many of which outline specific interpersonal behaviors and psychological pathways that may give rise to good or poor health. In this article, we argue that the study of relationships and health can move toward interrogating these mechanisms with greater precision and detail, but doing so will require a shift in the nature of commonly used research methods in this area. Accordingly, we draw heavily on the science of behavior change and discuss six key methodologies that may galvanize the mechanistic study of relationships and health: dismantling studies, factorial studies, experimental therapeutics, experimental mediation research, multiple assessments, and recursive modeling. We provide empirical examples for each strategy and outline new ways in which a given approach may be used to study the mechanisms linking intimate relationships and health. We conclude by discussing the key challenges and limitations for using these research strategies as well as novel ideas about how to integrate this work into existing paradigms within the field.

An Improved Bayesian Learning Method for Multi-agent System

A multi-agent coordinate ion is addressed in urban traffic control, which uses the recursive modeling method (RMM) that enables an agent to select its rational act ion by examining with other agents by modeling their decision making in a distributed multi-agent environment. Bayesian learning is used in conjunction with RMM for belief update. Based on this method, a multi-agent traffic control system is established and the results rated its effective.