Recursive utility for stochastic trees
成果类型：
Article
署名作者：
Hazen, GB; Pellissier, JM
署名单位：
Loyola University Chicago
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.44.5.788
发表日期：
1996
页码：
788-809
关键词：
摘要：
Stochastic trees are semi-Markov processes represented using tree diagrams. Such trees have been found useful for prescriptive modeling of temporal medical treatment choice. We consider utility functions over stochastic trees which permit recursive evaluation In a graphically intuitive manner analogous to decision tree rollback. Such rollback is computationally intractable unless a low-dimensional preference summary exists. We present the most general classes of utility functions having specific tractable preference summaries. We examine three preference summaries - memoryless, Markovian, and semi-Markovian - which promise both computational feasibility and convenience in assessment. Their use is illustrated by application to a previous medical decision analysis of whether to perform carotid endarterectomy.