Page 50 - DCAP310_INTRODUCTION_TO_ARTIFICIAL_INTELLIGENCE_AND_EXPERT_SYSTEMS

Introduction to Artificial Intelligence & Expert Systems

Notes Following points are remembered about knowledge acquisition:
I. The object of a knowledge representation is to express knowledge in a computer tractable
form, so that it can be used to enable our AI agents to perform well.

II. A knowledge representation language is defined by two aspects:
(i) Syntax: The syntax of a language defines which configurations of the components of
the language constitute valid sentences.

(ii) Semantics: The semantics defines which facts in the world the sentences refer to, and
hence the statement about the world that each sentence makes.
III. Suppose the language is arithmetic, then ‘x’, ‘=’ and ‘y’ are components (or symbols or
words) of the language the syntax says that ‘x = y’ is a valid sentence in the language, but
‘= = x y’ is not the semantics say that ‘x = y’ is false if y is bigger than x, and true otherwise

IV. The requirements of a knowledge representation are as follows:
(i) Representational Adequacy: The ability to represent all the different kinds of knowledge
that might be needed in that domain.

(ii) Inferential Adequacy: The ability to manipulate the representational structures to
derive new structures (corresponding to new knowledge) from existing structures.
(iii) Inferential Efficiency: The ability to incorporate additional information into the
knowledge structure which can be used to focus the attention of the inference
mechanisms in the most promising directions.

(iv) Acquisitional Efficiency: The ability to acquire new information easily. Ideally, the
agent should be able to control its own knowledge acquisition, but direct insertion
of information by a ‘knowledge engineer’ would be acceptable. Finding a system
that optimizes these for all possible domains is not going to be feasible.
V. In practice, the theoretical requirements for good knowledge representations can usually
be achieved by dealing appropriately with a number of practical requirements:
(i) The representations need to be complete – so that everything that could possibly
need to be represented can easily be represented.
(ii) They must be computable – implementable with standard computing procedures.
(iii) They should make the important objects and relations explicit and accessible – so
that it is easy to see what is going on, and how the various components interact.
(iv) They should suppress irrelevant detail – so that rarely used details don’t introduce
unnecessary complications, but are still available when needed.

(v) They should expose any natural constraints – so that it is easy to express how one
object or relation influences another.
(vi) They should be transparent – so you can easily understand what is being said.

(vii) The implementation needs to be concise and fast – so that information can be stored,
retrieved and manipulated rapidly.
VI. The four fundamental components of a good representation:

(i) The lexical part – that determines which symbols or words are used in the
representation’s vocabulary.
(ii) The structural or syntactic part – that describes the constraints on how the symbols
can be arranged, i.e. a grammar.

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