NSF Workshop: Bridging the Gap Between Operations Research and Approximate Dynamic Programming, April 16-20, 2005, in Cancun, Mexico

Princeton University, Princeton NJ

Investigators

Abstract

Dynamic programming has long held the promise of solving some of the more challenging decision problems. However, these approaches have suffered from the well known "curse of dimensionality" which essentially limits their applicability to decision problems with a few state variables. Recent advances in approximating these decision problems have led to methods known as approximate dynamic programming. These methods are intimately related to several other methods such as linear programming, and stochastic programming. This workshop will explore connections among these methods, as well as several important applications arising in transportation, power systems, and others. This workshop will bring together researchers and students from several disciplines, such as artificial intelligence, neural networks, and operations research to focus on new breakthroughs in approximate dynamic programming, and related areas.