By Ryszard S. Michalski, Jaime G. Carbonell and Tom M. Mitchell (Auth.)
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Additional resources for Machine Learning. An Artificial Intelligence Approach, Volume I
A characteristic description is a description of a class of objects (or situations, events, and so on) that states facts that are true of all objects in the class. It is usually intended to discriminate objects in the given class from objects in all other possible classes. For example, a characteristic description of the set of all tables would discriminate any table from all things that are non-tables. In this DIETTERICH & MICHALSK! 45 way, the description characterizes the concept of a table.
So there's a very impressive example of a learning program going back twenty-five years. Let me submit that however fine this program was from an AI standpoint, it only made sense if we really didn't understand checkers. If Samuel had understood checkers well, he could have put the final evaluation function in right at the beginning. (You may recall that he used two kinds of learning, but the only one I want to mention at the moment is tuning the evaluation function for positions on the basis of outcomes.
Structural descriptions portray objects as composite structures consisting of various components. For instance, a structural description of a building could represent the building in terms of the floors, the walls, the ceilings, the hallways, the roof, and so forth, along with the relations that hold among these various components. Structural descriptions can be contrasted with attribute descriptions, which specify only global properties of an object. An attribute description of a building might list its cost, architect, height, total square-footage and so forth.