  In AI research, so far, the attention paid to the characterization and
representation of function and affordance has been sporadic and sparse, even
though this aspect features prominently in an intelligent system's functioning.
In the sporadic and sparse, though commendable efforts so far devoted to the
characterization and understanding of function and affordance, there has also
been no general framework that could unify all the different use domains and
situations related to the representation and application of functional
concepts. This paper develops just such a general framework, with an approach
that emphasizes the fact that the representations involved must be explicitly
cognitive and conceptual, and they must also contain causal characterizations
of the events and processes involved, as well as employ conceptual constructs
that are grounded in the referents to which they refer, in order to achieve
maximal generality. The basic general framework is described, along with a set
of basic guiding principles with regards to the representation of
functionality. To properly and adequately characterize and represent
functionality, a descriptive representation language is needed. This language
is defined and developed, and many examples of its use are described. The
general framework is developed based on an extension of the general language
meaning representational framework called conceptual dependency. To support the
general characterization and representation of functionality, the basic
conceptual dependency framework is enhanced with representational devices
called structure anchor and conceptual dependency elaboration, together with
the definition of a set of ground level concepts. These novel representational
constructs are defined, developed, and described. A general framework dealing
with functionality would represent a major step toward achieving Artificial
General Intelligence.
