The name is absent



Semantic dimension: In GNOWSYS we can store propositions in three
layers with increasing order of semantics and consistency. The first
layer consists of simple propositions in the form of
well formed for-
mulae
(WFF). In the first layer, all kinds of propositions are allowed
to store without any semantic constraints. In the second layer, these
WFF can then be combined with the semantic constraints, logical con-
nectives, modalities, propositional attitudes, quantifiers etc. The sys-
tem does not check for contradictions, and consistencies in this layer
too, but consistency is implicit and therefore referred to as
implicit
structured system
(ISS). In the third layer, the validity constraints are
imposed
explicitly and therefore gives rise to explicit consistent systems
(ECS), which is quite similar to the experts’ knowledge system. This
way GNOWSYS proposes to represent knowledge of novices and ex-
perts, with the assumption that the ECS matches that of an expert and
the loosely structured ISS representation with that of novice. The se-
mantic dimension is not represented in the figure. Since it is possible
to build different ontologies from a given set of vocabulary and WFF,
it is possible to store multiple ontologies and epistemologies within a
single or a distributed knowledge base.

Complexity dimension: Along the complexity dimension, the system sup-
ports vocabularies like simple terms, and predicates, and very com-
plex forms like rules, arguments, axiomatic systems and other com-
plex compositions. The basic components provided are ObjectType
(OT), Object (O), RelationType (RT), Relation (R), MetaType (MT),
EventType (ET), Event (E), FlowType (FT), Flow (F), which helps to
store the terms, propositions and procedures. Complex compositions
are provided by the structure groups consisting of ProcessType (PT),
Process (P), StructureType (ST), Structure (S), Encapsulated Class,
Programs and ProgramType.

Inference dimension: Epistemic values such as validity and truth can be
checked along the inference dimension of GNOWSYS. Based on the
rules, and axioms it is possible to deduce consequences using deduc-
tive inference. It is also possible to add ampliative (induction and ab-
duction) and analogical inference engines to the system. This module
is not part of the core system but any existing inference engines can
be employed using the communication interface of GNOWSYS.



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