Foundations Of Cognitive Science

Means-Ends Analysis

Means-ends analysis is a problem solving strategy that arose from the work on problem solving of Newell and Simon (1972).  In means-ends analysis, one solves a problem by considering the obstacles that stand between the initial problem state and the goal state.  The elimination of these obstacles (and, recursively, the obstacles in the way of eliminating these obstacles) are then defined as (simpler) subgoals to be achieved.  When all of the subgoals have been achieved – when all of the obstacles are out of the way – then the main goal of interest has been achieved.  Because the subgoals have been called up by the need to solve this main goal, means-ends analysis can be viewed as a search strategy in which the long-range goal is always kept in mind to guide problem solving.  It is not as near-sighted as other search techniques, like hill climbing.

Means-ends analysis is a version of divide-and-conquer.  The difference between the two is that divide-and-conquer is purely recursive: the subproblems that are solved are always of the same type.  Means-ends analysis is more flexible, and less obviously recursive, because the subproblems that are defined for it need not all be of the same type.


  1. Newell, A., & Simon, H. A. (1972). Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall.

    (Added September 2010)