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OF THE DISSERTATION LEARNING DATA-DRIVEN MODELS OF NON-VERBAL BEHAVIORS FOR BUILDING RAPPORT USING AN INTELLIGENT VIRTUAL AGENT by Reza Amini Florida International University, 2015 Miami, Florida Professor Christine Lisetti, Major Professor There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. Excessive alcohol use is the third leading preventable cause of death in the United States, and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues can often be prevented with relatively simple lifestyle changes, such as learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent