Means-Ends Analysis

Means-Ends Analysis, a technique that was first used in Newell and Simon's General Problem Solver (GPS), is a problem-solving technique in which the current state is compared to the goal state, and the difference between them is divided up into subgoals in order to achieve the goal state by the use of the available operators. Means-End analysis is one of many weak search methods that have been utilized in both cognitive architectures and more general artificial intelligence research.

The following architectures support the use of Means-End Analysis:

Planning and Learning Architecture (Prodigy)
Problem Space Architecture (Soar)
Modular, Integrated Architecture (ICARUS)

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