TY - GEN
T1 - Approximate dynamic programming in knowledge discovery for rapid response
AU - Frazier, Peter
AU - Powell, Warren
AU - Dayanik, Savas
AU - Kantor, Paul
PY - 2009
Y1 - 2009
N2 - One knowledge discovery problem in the rapid response setting is the cost of learning which patterns are indicative of a threat. This typically involves a detailed follow-through, such as review of documents and information by a skilled analyst, or detailed examination of a vehicle at a border crossing point, in deciding which suspicious vehicles require investigation. Assessing various strategies and decision rules means we must compare not only the short term effectiveness of interrupting a specific traveler, or forwarding a specific document to an analyst, but we must also weigh the potential improvement in our profiles that results even from sending a "false alarm". We show that this problem can be recast as a dynamic programming problem with, unfortunately, a huge state space. Several specific heuristics are introduced to provide improved approximations to the solution. The problems of obtaining real-world data to sharpen the analysis are discussed briefly.
AB - One knowledge discovery problem in the rapid response setting is the cost of learning which patterns are indicative of a threat. This typically involves a detailed follow-through, such as review of documents and information by a skilled analyst, or detailed examination of a vehicle at a border crossing point, in deciding which suspicious vehicles require investigation. Assessing various strategies and decision rules means we must compare not only the short term effectiveness of interrupting a specific traveler, or forwarding a specific document to an analyst, but we must also weigh the potential improvement in our profiles that results even from sending a "false alarm". We show that this problem can be recast as a dynamic programming problem with, unfortunately, a huge state space. Several specific heuristics are introduced to provide improved approximations to the solution. The problems of obtaining real-world data to sharpen the analysis are discussed briefly.
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U2 - 10.1109/HICSS.2009.79
DO - 10.1109/HICSS.2009.79
M3 - Conference contribution
AN - SCOPUS:78650760923
SN - 9780769534503
T3 - Proceedings of the 42nd Annual Hawaii International Conference on System Sciences, HICSS
BT - Proceedings of the 42nd Annual Hawaii International Conference on System Sciences, HICSS
T2 - 42nd Annual Hawaii International Conference on System Sciences, HICSS
Y2 - 5 January 2009 through 9 January 2009
ER -