Article ID: | iaor1999813 |
Country: | United States |
Volume: | 54 |
Issue: | 3 |
Start Page Number: | 183 |
End Page Number: | 200 |
Publication Date: | Jul 1997 |
Journal: | Computer Methods and Programs in Biomedicine |
Authors: | Magni P., Bellazzi R. |
Keywords: | markov processes, control processes |
The problem of formulating plans under uncertainty and coping with dynamic decision problems is a major task of both artificial intelligence and control theory applications in medicine. In this paper we will describe a software package, called DT-Planner, designed to represent and solve dynamic decision problems that can be modelled as Markov decision processes, by exploiting a novel graphical formalism, called influence view. An influence view is a directed acyclic graph that depicts the probabilistic relationships between the problem state variables in a generic time transition; additional variables, called event variables, may be added, in order to describe the conditional independences between state variables. By using the specified conditional independence structure, an influence view may allow a parsimonious specification of a Markov decision process. DT-Planner lets the user specify and manage models through a user-friendly graphical interface, and implements efficient for policy determination algorithms. DT-Planner is written in C with Open Interface(TM) libraries and can be obtained, for non commercial use, via anonymous ftp without charge.