Using Conditional Random Fields for Decision-Theoretic Planning

Abstract

We propose a means of extending Conditional Random Field modeling to decision-theoretic planning where valuation is dependent upon fully observable factors. Representation is discussed, and a comparison with existing decision problem methodologies is presented. Included are exact and inexact message passing schemes for policy making, examples of decision making in practice, extensions to solving general decision problems, and suggestions for future use