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Unit 3: Representation of Knowledge
In the Figure 3.1 all the objects are within ovals and connected using labelled arcs. Note that Notes
there is a link between Jill and FemalePersons with label MemberOf. Similarly, there is a
MemberOf link between Jack and MalePersons and SisterOf link between Jill and Jack. The
MemberOf link between Jill and FemalePersons indicates that Jill belongs to the category of
female persons.
Inheritance Reasoning
Unless, there is a specific evidence to the contrary, it is assumed that all members of a class
(category) will inherit all the properties of their superclasses. So semantic network allows us to
perform inheritance reasoning. For example, Jill inherits the property of having two legs as she
belongs to the category of FemalePersons which, in turn, belongs to the category of Persons
which has a boxed Legs link with value 2. Semantic nets allows multiple inheritance. So an
object can belong to more than one category and a category can be a subset of more than one
another category.
Inverse Links
Semantic network allows a common form of inference known as inverse links. For example, we
can have a HasSister link which is the inverse of SisterOf link. The inverse links make the job of
inference algorithms much easier to answer queries such as who the sister of Jack is. On
discovering that HasSister is the inverse of SisterOf the inference algorithm can follow that link
HasSister from Jack to Jill and answer the query.
Disadvantage of Semantic Nets
One of the drawbacks of semantic network is that the links between the objects represent only
binary relations. For example, the sentence Run(ChennaiExpress, Chennai,Bangalore,Today)
cannot be asserted directly.
There is no standard definition of link names.
Advantages of Semantic Nets
Semantic nets have the ability to represent default values for categories. In the figure, Jack has
one leg while he is a person and all persons have two legs. So persons have two legs has only
default status which can be overridden by a specific value.
Semantic nets convey some meaning in a transparent manner.
Semantic nets are simple and easy to understand.
Semantic nets are easy to translate into PROLOG.
3.1.2 Frames and Scripts
Two other popular knowledge representation formalisms are frames and scripts. Although,
these were developed independently (both originating in the early 1970s), and are different in
important ways, they have sufficient similarities to be considered together. One influential
proponent of frame-based systems is Marvin Minsky (1975); a champion of script-based systems
is Roger Schank (see Schank and Abelson, 1977). The key idea involved in both frames and
scripts is that our knowledge of concepts, events, and situations is organized around expectations
of key features of those situations.
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