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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Dynamic programming offers an elegant, unified treatment of a wide range of stochastic control problems. However, the curse of dimensionality gives rise to prohibitive computational requirements that render infeasible the exact solution of large--scale problems. We study an efficient method based on linear programming for approximating solutions to such problems. The approach "fits'" a linear combination of pre--selected basis functions to the dynamic programming cost--to--go function. We develop error bounds that offer performance guarantees and also guide the selection of both basis functions and "state--relevance weights'' that influence quality of the approximation. Experimental results in queueing problems and an application to web server farms provide empirical support for the methodology.
