Advances in approximate and adaptive dynamic programming

根据这一建议进行的研究将推进理论和应用。 它将专注于复杂的问题，在不确定性下的顺序决策，特别注意先进的方法来解决大问题（近似动态规划）和学习系统参数的方法在决策过程中（自适应动态规划）。 对于近似动态规划，它将提供新的边界近似解沿着几个理论和实际结果。 近似动态规划在医疗保健管理和在线拍卖中的新应用将补充理论上的进步，并为使用这些方法的实际方面提供进一步的见解。 自适应动态规划方法将应用于前列腺癌治疗和通过互联网拍卖销售的问题。 这项研究的应用，以解决医疗保健问题的重要管理挑战，有效利用稀缺资源。这一领域的创新将对加拿大人今天面临的首要问题产生重大影响;及时获得高质量的医疗服务。

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.