Decision making in fuzzy discrete event systems

  • Authors:

  • F. Lin;H. Ying;R. D. MacArthur;J. A. Cohn;D. Barth-Jones;L. R. Crane

  • Affiliations:

  • Department of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USA and School of Electronics and Information Engineering, Tongji University, Shanghai, China;Department of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USA;Department of Medicine, Wayne State University, Detroit, MI 48202, USA;Department of Medicine, Wayne State University, Detroit, MI 48202, USA;Department of Medicine, Wayne State University, Detroit, MI 48202, USA and Center for Healthcare Effectiveness Research, Wayne State University, Detroit, MI 48202, USA;Department of Medicine, Wayne State University, Detroit, MI 48202, USA

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2007

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Abstract

The primary goal of the study presented in this paper is to develop a novel and comprehensive approach to decision making using fuzzy discrete event systems (FDES) and to apply such an approach to real-world problems. At the theoretical front, we develop a new control architecture of FDES as a way of decision making, which includes a FDES decision model, a fuzzy objective generator for generating optimal control objectives, and a control scheme using both disablement and enforcement. We develop an online approach to dealing with the optimal control problem efficiently. As an application, we apply the approach to HIV/AIDS treatment planning, a technical challenge since AIDS is one of the most complex diseases to treat. We build a FDES decision model for HIV/AIDS treatment based on expert's knowledge, treatment guidelines, clinic trials, patient database statistics, and other available information. Our preliminary retrospective evaluation shows that the approach is capable of generating optimal control objectives for real patients in our AIDS clinic database and is able to apply our online approach to deciding an optimal treatment regimen for each patient. In the process, we have developed methods to resolve the following two new theoretical issues that have not been addressed in the literature: (1) the optimal control problem has state dependent performance index and hence it is not monotonic, (2) the state space of a FDES is infinite.