Time Sensitive Sequential Myopic Information Gathering

DIGS (Decision Support Information Gathering System) uses the value of information to guide the information gathering process and uses the gathered information to provide the decision recommendations to the human users. DIGS uses an influence diagram as a modeling tool. In this paper, we create a model to represent the investment scenario of a novice stock investor. By using the sequential myopic information gathering technique, DIGS generates a sequence of information gathering actions. The actions are dependent on each other in that the action DIGS executes at time t1 will be based on the results of the pervious action at time t0. DIGS also employs a stopping mechanism for the information gathering actions based on the information value and time constraints. Thus, DIGS can be used as an anytime system. Compared to a pre-generated sequence of actions, our technique has the flexibility to react to the gathered information, and to use it to guide the subsequent gathering actions. Therefore, our system can adapt to the newly acquired information and avoid the computational complexity of planning the series of actions in advance.