Control engineering offers a systematic and efficient approach to optimizing the effectiveness of individually tailored treatment and prevention policies, also known as adaptive or ``just-in-time'' behavioral interventions. These types of interventions represent promising strategies for addressing many significant public health concerns. This dissertation explores the development of decision algorithms for adaptive sequential behavioral interventions using dynamical systems modeling, control engineering principles and formal optimization methods.
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- Partial requirement for: Ph.D., Arizona State University, 2014Note typethesis
- Includes bibliographical references (p. 223-231)Note typebibliography
- Field of study: Chemical engineering