(Artificial Intelligence)
Knowledge
Types of knowledge in AI
Issues of Knowledge Representation
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Knowledge is a familiarity, awareness or
understanding of someone or something, such
as facts, information, descriptions, or skills,
which is acquired through experience or
education by perceiving, discovering, or
learning
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Knowledge is the body of facts and principles.
Knowledge can be language, concepts,
procedures, rules, ideas, abstractions, places,
customs, and so on. study of knowledge is
called Epistemology.
There are 5 main types of knowledge
representation in Artificial Intelligence.
 Meta Knowledge
 Heuristic - Knowledge
 Procedural Knowledge
 Declarative Knowledge
 Structural Knowledge
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Its a knowledge about a knowledge and how to
gain them.
Meta-knowledge includes information about
the knowledge the system possesses, about the
efficiency of certain methods used by the
system, the probabilities of the success of past
plans, etc. The meta-knowledge is generally
used to guide future planning or execution
phases of a system.

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Heuristic refers to experience-based
techniques for problem solving, learning, and
discovery that give a solution which is not
guaranteed to be optimal.
Where the exhaustive search is impractical,
heuristic methods are used to speed up the
process of finding a satisfactory solution via
mental shortcuts to ease the cognitive load of
making a decision.
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Examples of this method include using a rule
of thumb, an educated guess, an intuitive
judgment, stereotyping, or common sense
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In artificial intelligence, procedural knowledge
is compiled or processed form of information.
Procedural knowledge is related to the
performance of some task. For example,
sequence of steps to solve a problem is
procedural knowledge.
A well-known example is the Procedural
Reasoning System, which might, in the case of
a mobile robot that navigates in a building,
contain procedures such as "navigate to a
room" or "plan a path"
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Declarative knowledge is passive knowledge in
the form of statements of facts about the world.
For example, mark statement of a student is
declarative knowledge.
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Structural knowledge is built with schemas
and interrelated schemas (schemata).
through schema selection or inheritance of
attributes from other schemas in order to
acquire structural knowledge.
Describes what relationship exists between
concepts/ objects.
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AI agents deal with knowledge (data)
Facts (believe & observe knowledge)
Procedures (how to knowledge)
Meaning (relate & define knowledge)

Any intelligent entity that wishes to reason
about its world encounters an important,
inescapable fact: reasoning is a process that
goes on internally, while most things it wishes
to reason about exist only externally.

A program (or person) engaged in planning the
assembly of a bicycle, for instance, may have to
reason about entities like wheels, chains,
sprockets, handle bars, etc., yet such things
exist only in the external world.
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Knowledge level debugging
Infinite loops
Querying the user
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Just as in other software, there can be errors
and omissions in knowledge bases. Domain
experts and knowledge engineers must be able
to debug a knowledge base and add
knowledge.

In knowledge-based systems, debugging is
difficult because the domain experts and users
who have the domain knowledge required to
detect a bug do not necessarily know anything
about the internal working of the system, nor
do they want to.

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For example, debugging a medical knowledge
base should be a question of medicine that
medical experts, who are not experts in AI, can
answer.
Similarly, debugging a knowledge base about
house wiring should be with reference to the
particular house, not about the internals of the
system reasoning with the knowledge base.
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There is an infinite loop in the top-down
derivation if there is an atom a that is being
proved as a subgoal of a. (Here we assume that
being a subgoal is transitive; a subgoal of a
subgoal is a subgoal).
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Thus, there can be an infinite loop only if the
knowledge base is cyclic. A knowledge base is
cyclic if there is an atom a such that there is a
sequence of definite clauses of the form
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a ←...a1 ...
a1 ←...a2 ...
...
an ←...a ...
(where if n=0 there is a single definite clause
with a in the head and body).
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At design time or offline, there is typically no
information about particular cases. This
information arrives online from users, sensors,
and external knowledge sources.

For example, a medical-diagnosis program
may have knowledge represented as definite
clauses about the possible diseases and
symptoms but it would not have knowledge
about the actual symptoms manifested by a
particular patient
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he idea of querying the user is that the system
can treat the user as a source of information
and ask the user specific questions about a
particular case. The proof procedure can
determine what information is relevant and
will help to prove a query.