Stochastic Systems Group
Home Research Group Members Programs  
Demos Calendar Publications Mission Statement Alumni

SSG Seminar Abstract

Applications of Approximate Dynamic Programming to Problems of Sensor Management

Dr. Michael Schneider - Alphatech, Inc.

This talk describes some techniques for addressing the problem of controlling a sensor to collect data so as to estimate the states of objects, which are dynamically changing. The techniques described include both exact and approximate ones. In particular, classical results on multiarmed bandit scheduling characterize the optimal control for some special infinite-horizon problems. An extension of these results we have developed for finite-horizon problems is overviewed in the talk. Also included will be a discussion of the applicability of rollout approximate dynamic programming techniques to sensor management. Such approach will be illustrated with an example sensor management problem from air-to-ground surveillance.

Associated conference papers:

M. K. Schneider, G. L. Mealy, and F. M. Pait. Closing the loop in sensor fusion systems: Stochastic dynamic programming approaches. In Proceedings of the American Control Conference, 2004

R. B. Washburn, M. K. Schneider, and J. Fox. Stochastic Dynamic Programming Based Approaches to Sensor Resource Management. In Proceedings of the International Conference on Information Fusion, Annapolis, 2002.

Problems with this site should be emailed to