The first one incorporates information about past experiences into simplified models of the world, and then uses the models to steer decisions through search-space based upon a sort of back-of-the-envelope, hazy calculation of expected value. It's a utility function, basically, as implemented by brain.

The second one also incorporates information about past experiences, but rather than constructing the dataset into a model and performing searches over it, it derives expectations directly from what's remembered, and is insensitive to things like probability or shifting subjecting values.

The third one is sort of like the first in its basic operations (incorporate information, analyze it, make models) -- but instead of calculating expected values, it aims to satisfy various inbuilt "drives", and sorts paths through search space based upon approach/avoid criteria linked to those drives.