Means-end analysis. Generally search strategies can reason either forward or backward for a given problem. But in certain situations, a mixture of the two direction is appropriate. Such a mixed strategy would make it possible to to solve the major parts of a problem first and then go back and solve the small problems that arise in "gluing" the big pieces together. The means-end analysis allows us to do that. The problem space of means-end analysis has an initial state (object) and one or more goal states (objects), a set of operators O_k with given preconditions for their application, and a difference function that computes the difference between two states Si and Sg. A problem is solved using means-end analysis by:

1. Comparing the current state Si to a goal state Sg and computing the difference Dig.
2. An operator O_k is then selected to reduce the difference Dig.
3. The operator O_k is applied if possible. If not, the current state is saved, a sub-goal is created and means-end analysis is applied recursively to reduce the sub-goal.
4. If the sub-goal is solved the saved state is restored and work is resumed on the original problem.