• Start Date: July 3, 2008
• Event Start Time: 12:00 PM
• Event End Time: 1:00 PM
• Organizers: Christine Agnese
• Seminar Series: REU Seminar
• Presenter(s): Fred Roberts - Rutgers University
• Event Location: DIMACS Seminar room
• Abstract: As a stream of containers arrives at a port, a decision maker has to decide how to inspect them, which to subject to further inspection, which to allow to pass through with only minimal levels of inspection, etc. We look at this as a complex sequential decision making problem. Sequential decision problems arise in many areas, including communication networks, manufacturing, artificial intelligence and computer science, and medicine. The problem we investigate is to find algorithms for sequential diagnosis that minimize the total "cost" of the inspection procedure, including the cost of false positives and false negatives. To make the problem precise, we imagine a stream of containers arriving at the port with the goal of classifying each of them into one of several categories. There are several possible tests that can be performed and an inspection scheme specifies which test to perform next based on outcomes of previous tests. Stroud and Saeger at Los Alamos have formulated this problem, in an important special case, as a problem of finding an optimal binary decision tree for an appropriate binary decision function. We describe the basic idea of the Stroud-Saeger method and the results of new algorithms that improve significantly on the size of the decision problems for which it is applicable.