Question

I am currently reading “Artificial Intelligence: A modern Approach”. Though the terminology factored, structured and atomic representation is confusing what do these mean exactly?

In relation with programming…

Thanks

Answer 1

I’m not thrilled with the lines that Russell and Norvig draw, but: Generally, when you’re using AI techniques to solve a problem, you’re going to have a programmed model of the situation. Atomic/factored/structured is a qualitative measure of how much “internal structure” those models have, from least to most.

Atomic models have no internal structure; the state either does or does not match what you’re looking for. In a sliding tile puzzle, for instance, you either have the correct alignment of tiles or you do not.

Factored models have more internal structure, although exactly what will depend on the problem. Typically, you’re looking at variables or performance metrics of interest; in a sliding puzzle, this might be a simple heuristic like “number of tiles out of place,” or “sum of manhatten distances.”

Structured models have still more; again, exactly what depends on the problem, but they’re often relations either of components of the model to itself, or components of the model to components of the environment.

It is very easy, especially when looking at very simple problems like the sliding tile, to unconsciously do all the hard intelligence work yourself, at a glance, and forget that your model doesn’t have all your insight. For example, if you were to make a program to do a graph search technique on the sliding puzzle, you’d probably make some engine that took as input a puzzle state and an action, and generated a new puzzle state from that. The puzzle states are still atomic, but you the programmer are using a much more detailed model to link those inputs and outputs together.