Control of fuzzy discrete event systems and its applications to clinical treatment planning

In this paper, we further develop a modeling and control approach to fuzzy discrete event systems that we initially proposed in Lin, F. and H. Ying, (2001), (2002). We first investigate an optimal control problem in fuzzy discrete event systems. The problem is abstracted from real applications in biomedical fields. The control objective is to maximize a treatment effectiveness measure while keeping some cost below a given level. This problem is difficult because both the effectiveness function and the cost function are state dependent and hence are not monotonic. Furthermore, the state space of a fuzzy discrete event system is infinite in general. We develop an online approach that can solve this problem. We then apply this approach to HIV/AIDS treatment planning, because it is one of the most difficult treatments in medicine. We also develop a novel computerized treatment decision-making system based on the optimal control approach. The preliminary statistic evaluation of our system shows a strong agreement between the physicians and our system in terms of which treatment regimens to be used for patients of various conditions.