Means-ends Analysis - Some AI Systems Using MEA

Some AI Systems Using MEA

The MEA technique as a problem-solving strategy was first introduced in 1963 by Allen Newell and Herbert A. Simon in their computer problem-solving program General Problem Solver (GPS). In that implementation, the correspondence between differences and actions, also called operators, is provided a priori as knowledge in the system. (In GPS this knowledge was in the form of table of connections.)

When the action and side-effects of applying an operator are penetrable, the search may select the relevant operators by inspection of the operators and do without a table of connections. This latter case, of which the canonical example is STRIPS, an automated planning computer program, allows task-independent correlation of differences to the operators which reduce them.

Prodigy, a problem solver developed in a larger learning-assisted automated planning project started at Carnegie Mellon University by Jaime Carbonell, Steven Minton and Craig Knoblock, is another system that used MEA.

Professor Morten Lind, at Technical University of Denmark has developed a tool called multilevel flow modeling (MFM). It performs means-end based diagnostic reasoning for industrial control and automation systems.