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Konstantinos Tsiakas; Lynette Watts; Cyril Lutterodt; Theodoros Giannakopoulos; Alexandros Papangelis; Robert Gatchel; Vangelis Karkaletsis; Fillia Makedon (2015)
Publisher: Association for Computing Machinery (ACM)
Types: Conference object
Subjects: Adaptive Dialogue Systems, Markov Decision Processes, Reinforcement Learning

Classified by OpenAIRE into

ACM Ref: InformationSystems_MODELSANDPRINCIPLES
In this paper, we present an Adaptive Multimodal Dialogue System for Depressive and Anxiety Disorders Screening (DADS). The system interacts with the user through verbal and non-verbal communication to elicit the information needed to make referrals and recommendations for depressive and anxiety disorders while encouraging the user and keeping them calm. We designed the problem using interconnected Markov Decision Processes using sub-goals to deal with the large state space. We present the problem formulation and the experimental procedure for the training data collection and the system training following the methodology of Wizard-of-Oz experiments.
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