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arXiv · 1706.02897

Bandit Models of Human Behavior: Reward Processing in Mental Disorders

Djallel Bouneffouf·Irina Rish·Guillermo A. Cecchi
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Abstract

Drawing an inspiration from behavioral studies of human decision making, we propose here a general parametric framework for multi-armed bandit problem, which extends the standard Thompson Sampling approach to incorporate reward processing biases associated with several neurological and psychiatric conditions, including Parkinson's and Alzheimer's diseases, attention-deficit/hyperactivity disorder (ADHD), addiction, and chronic pain. We demonstrate empirically that the proposed parametric approach can often outperform the baseline Thompson Sampling on a variety of datasets. Moreover, from the behavioral modeling perspective, our parametric framework can be viewed as a first step towards a unifying computational model capturing reward processing abnormalities across multiple mental conditions.

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Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi. 2017-06-07. Bandit Models of Human Behavior: Reward Processing in Mental Disorders. https://arxiv.org/abs/1706.02897

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