Means-End Analysis

Means-End Analysis (MEA) is a heuristic technique used by AI systems to minimize the gap between the current state and the goal state.
It works by:

1. Comparing the current situation with the desired goal.
2. Identifying the difference.
3. Selecting an action that reduces this difference.

For instance, in a route-finding problem, if the goal is to reach a city, MEA may first suggest getting closer by taking a highway, then refine by choosing smaller connecting roads.

This approach mimics human-like reasoning, focusing on incremental progress rather than exhaustive search — making it a key strategy in expert systems and cognitive AI models.