Representing knowledge using
logical formalism, like predicate logic, has several advantages. They
can be combined with powerful inference mechanisms like resolution,
which makes reasoning with facts easy. But using logical formalism
complex structures of the world, objects and their relationships,
events, sequences of events etc. can not be described easily.
A good system for the representation of structured knowledge in a particular domain should posses the following four properties:
(i) Representational Adequacy:- The ability to represent all kinds of knowledge that are needed in that domain.
(ii) Inferential Adequacy :- The ability to manipulate the represented structure and infer new structures.
(iii) Inferential Efficiency:- The ability to incorporate additional information into the knowledge structure that will aid the inference mechanisms.
(iv) Acquisitional Efficiency :- The ability to acquire new information easily, either by direct insertion or by program control.
The techniques that have been developed in AI systems to accomplish these objectives fall under two categories:
1. Declarative Methods:-
In these knowledge is represented as static collection of facts which
are manipulated by general procedures. Here the facts need to be stored
only one and they can be used in any number of ways. Facts can be easily
added to declarative systems without changing the general procedures.
2. Procedural Method:-
In these knowledge is represented as procedures. Default reasoning and
probabilistic reasoning are examples of procedural methods. In these,
heuristic knowledge of “How to do things efficiently “can be easily
represented.
In practice
most of the knowledge representation employ a combination of both. Most
of the knowledge representation structures have been developed to handle
programs that handle natural language input. One of the reasons that
knowledge structures are so important is that they provide a way to
represent information about commonly occurring patterns of things . such
descriptions are some times called schema. One definition of schema is
“Schema refers
to an active organization of the past reactions, or of past experience,
which must always be supposed to be operating in any well adapted
organic response”.
By using
schemas, people as well as programs can exploit the fact that the real
world is not random. There are several types of schemas that have proved
useful in AI programs. They include
(i) Frames:- Used to describe a collection of attributes that a given object
possesses (eg: description of a chair).
(ii) Scripts:- Used to describe common sequence of events
(eg:- a restaurant scene).
(eg:- a restaurant scene).
(iii) Stereotypes :- Used to described characteristics of people.
(iv) Rule models:- Used to describe common features shared among a
set of rules in a production system.
set of rules in a production system.
Frames and
scripts are used very extensively in a variety of AI programs. Before
selecting any specific knowledge representation structure, the following
issues have to be considered.
(i) The basis properties of objects , if any, which are common to every problem domain must be
identified and handled appropriately.
identified and handled appropriately.
(ii) The entire knowledge should be represented as a good set of primitives.
(iii) Mechanisms must be devised to access relevant parts in a large knowledge base.
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