Advances in approximate and adaptive dynamic programming

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Research carried out under this proposal will advance theory and application.  It will focus on complex problems in sequential decision making under uncertainty paying special attention to advancing methods for solving large problems (approximate dynamic programming) and methods for learning system parameters in the course of the decision making process (adaptive dynamic programming).  For approximate dynamic programming, it will provide new bounds on approximate solutions along with several theoretical and practical results.  Novel applications of approximate dynamic programming to health care management and online auctions will complement the theoretical advances and provide further insight into the practical aspects of using these methods.  Adaptive dynamic programming methods will be applied to problems in prostate cancer treatment and selling through Internet auctions.   The applications of this research to healthcare issues address important management challenges concerning the efficient use of scarce resources. Innovations in this area will significantly impact the number one issue facing Canadians today; timely access to quality medical care.