Automatic Evaluation of Higher-Order Partial Derivatives for Nonlocal Sensitivity Analysis

This proceedings paper surveys work on the FEED (Fast Efficient Evaluation of Derivatives) algorithm originally developed by Kalaba, Tesfatsion, and Wang (1983), with particular reference to the use of FEED for the implementation of nonlocal automated sensitivity techniques; see the articles below. The relationship of FEED to the automatic differentiation algorithms developed by other SIAM Workshop participants is clarified. Related work can be accessed here: http://www.econ.iastate.edu/tesfatsi/nasahome.htm