Example of Means-Ends Analysis

   The figure to the right provides an example of some of the features of Means-Ends Analysis as it was employed in GPS. The example problem that we consider is to 'go from your house in New Brunswick to your Aunt's House in Los Angeles.' GPS required knowledge about the problem domain. This knowledge was represented in a Difference-Operator Table. This table provides the knowledge needed to decompose a problem into subproblems. An example of such a table is shown in the top portion of the figure. 

   The basic idea that underlies Means-Ends Analysis is that the planner has the ability to compare two problem states and determine one or more ways in which these problem states differ from each other. (These problem states are thought of as partial state descriptions. Even though partial, note that if we think of these problem states as a set of descriptions, then there are a great many ways in which to construct differences. Let Dif  be the union of the descriptions of the problem states with their intersection removed. Then, the number of possible descriptions of the way in which these problem states differ is approximated by the power set of  Dif.. ) The rows of this example table lists a way in which two problem states might differ. The labels at the top of the columns list an operator (action) that can reduce the difference. And, the labels at the bottom of the columns list the partial state description that must be satisfied in order for the operator to be applied. For example the top row lists the possibility that the two states are more than 1000 miles apart. For this difference only the first column is "Xed" indicating that only the operator associated with column one, 'use airplane' is considered appropriate to this difference. And, at the bottom of this column is listed the precondition associated with this operator; namely, to 'be at airport.'

   The remainder of this figure illustrates a "trace" of the recursive application of the Means End Analysis procedure. Note the "problem state names" depicted in the lower part of the figure. These are Sstart, Sa, ... , Sg, Sgoal. This alphabetical listing mirrors the order in which they were generated in the planning phase. Note that this is quite different from the execution ordering depicted by their location on the dotted red line. For example, Sa is the first intermediate problem state considered but it occurs in the middle of the time line that represents the order in which the actions must be executed.

   A careful study of the trace reveals the way in which this procedure can introduce "island states."


Planning - Table of Contents

 © Charles F. Schmidt