[1-2] Glossary of AI terms.

This is the start of a simple glossary of short definitions for AI terminology.

   ai:
        A three-toed sloth of genus Bradypus. This forest-dwelling
        animal eats the leaves of the trumpet-tree and sounds a
        high-pitched squeal when disturbed. (Based on the Random House
        dictionary definition.)

   Admissibility:
        An admissible search algorithm is one that is guaranteed to
        find an optimal path from the start node to a goal node, if
        one exists. In A* search, an admissible heuristic is one that never
        overestimates the distance remaining from the current node to
        the goal. 

   Case-based Reasoning: 
        Technique whereby "cases" similar to the current problem are
        retrieved and their "solutions" modified to work on the current
        problem. 

   Data Mining:
	Also known as Knowledge Discovery in Databases (KDD) was been defined
	as "The nontrivial extraction of implicit, previously unknown, and
	potentially useful information from data" in Frawley and
	Piatetsky-Shapiro's overview.  It uses machine learning, statistical
	and visualization techniques to discover and present knowledge in a
	form which is easily comprehensible to humans.

   Fuzzy Logic:
        In Fuzzy Logic, truth values are real values in the closed
        interval [0..1]. The definitions of the boolean operators are
        extended to fit this continuous domain. By avoiding discrete
        truth-values, Fuzzy Logic avoids some of the problems inherent in
        either-or judgments and yields natural interpretations of utterances
        like "very hot". Fuzzy Logic has applications in control theory.

   Nonlinear Planning:
        A planning paradigm which does not enforce a total (linear)
        ordering on the components of a plan.

   Strong AI:           
        Claim that computers can be made to actually think, just like human
        beings do. More precisely, the claim that there exists a class of
        computer programs, such that any implementation of such a program is
        really thinking.

   Validation:
        The process of confirming that one's model uses measureable inputs
        and produces output that can be used to make decisions about the
        real world.

   Verification:
        The process of confirming that an implemented model works as intended.

   Weak AI:             
        Claim that computers are important tools in the modeling and
        simulation of human activity.