In this section we define what knowledge bases and formalisms are. Since we want to consider formalisms that are very different both in syntax and in semantics, we need very general definitions. Let us consider, as a base case, the formalism of propositional calculus. Formally, we can assume that it is composed of three parts:
The syntax is defined from a finite alphabet of propositional
symbols
, possibly with subscripts, and the
usual set of propositional connectives
,
,
.
In terms of knowledge representation, the proof theory can be
seen as a way for extracting knowledge from a knowledge base.
For example, if our knowledge base is , then the
fact
holds. We can thus say that the formula
is part of the knowledge represented by
.
In some cases, we want knowledge bases to represent models
rather than sets of formulas. An interpretation for
an alphabet of propositional variables is a mapping from
in
. The model-theoretic
semantics of the propositional calculus is the usual way
of extending an interpretation for
to well-formed
formulas.
Let us now extend such definition to generic formalisms: a formalism is composed of a syntax, a proof theory, and a model-theoretic semantics.
We remark that each formalism has its own syntax: for instance,
default logic includes a ternary connective
for denoting default rules, while logic programming has a
special unary connective
, and so on. A knowledge base
of a formalism
is simply a well-formed formula, according
to the syntax of the formalism.
Each formalism has its own proof theory as well.
The proof theory of a formalism is a binary
relation
on the set of knowledge bases and formulae.
Intuitively,
means that
is a consequence
of the knowledge base
, according to the rules of the
formalism
. As a result, the set of formulae
that
are implied by a knowledge base
is exactly the knowledge
represented by
.
The base of a comparison between two different formalisms is
a concept of equivalence, allowing for saying that two knowledge
bases (of two different formalisms) represent the same piece of
knowledge. Since the knowledge represented by a knowledge base
is the set of formulas it implies, we have to assume that the
syntax of these formulae is the same for all formalisms. Namely,
we always assume that the formulae implied by a knowledge base
are well-formed formulae of the propositional calculus. In other
words, each formalism has a syntax for the knowledge bases:
however, we assume that the proof theory relates knowledge
bases (formulae in the syntax of the formalism) with propositional
formulae. So, while writing
, we assume that
is a knowledge base in the syntax of
, while
is
a propositional formula.
This allows for saying that two knowledge bases and
, expressed in two different formalisms
and
,
represent the same piece of knowledge: this is true when,
for any propositional formula
it holds
if and only if
.
The model-theoreric semantics of a formalism is a relation
between propositional models and knowledge bases. In
this case, we assume a fixed alphabet
, thus the set of all
interpretations is common to all formalisms. When a model
and
a knowledge base
are in the relation, we write
.
Intuitively, this means that the model
supports the piece of
knowledge represented by
.
We remark that some formalisms, e.g. credolous default logic [45], have a proof theory, but do not have a model-theoretic semantics. It is also possible to conceive formalisms with a model-theoretic semantics but no proof theory. When both of them are defined, we assume that they are related by the following formula:
Regarding the proof theory of formalisms, we only consider
formulae that are shorter than the knowledge base, that is,
we assume that the knowledge represented by a knowlegde base
is the set of formulae
such that
,
and the size of
is at most the size of
. This is
done for two reasons: first, formulas that are larger than
are likely to contain large parts that are actually
independent from
; second, we can give technicals result
in a very simple way by using the compilability classes
introduced in the next section.
We consider only formulae whose size is less than or equal to that of the knowledge base.
All formalisms we consider satisfy the right-hand side
distruibutivity of conjunction, that is,
if and only if
and
.
The assumption on the size of
is not restrictive in
this case, if
is a CNF formula.