Know what knowledge representation and reasoning is field of Soft Computing !

1. What is Knowledge Representation and Reasoning
?

2. • In the world of Artificial Intelligence, Knowledge representation is that area in which information
about the world is given in such a form that the computer system can understand and can leverage
it in performing complex tasks like diagnosing a medical condition or having a dialog in natural
language.
• Knowledge representation simplifies the complex system for better design and development by
studying human psychology and the way humans solve their problems.
• Semantic nets, systems architecture, frames, rules and ontologies can be considered as examples
of knowledge representation.
What is Knowledge Representation and Reasoning
?

3. • Knowledge representation goes parallel with automated reasoning. This is due to the aim of
knowledge representation, i.e. to be able to reason about that knowledge, assert new knowledge
etc.
• All the knowledge representation languages that are known feature reasoning, as it is its integral
part.
• Expressivity and practicality are those chunks of knowledge representation between trade-off has to
be set when design is considered.
• First Order Logic (FOL) is the ultimatum of knowledge representation formalism in terms of
expressive power and compactness.
• However, anything, no matter how good, has some setbacks and so does FOL- ease of use and
practicality of implementation.
Cont….

4. 1. Primitives- Semantic networks belongs the circle of knowledge representation primitives. For
general fast search, data structures and algorithms were used. In the incunabula of knowledge
representation, Lisp programming language was modeled after the lambda calculus and was very
frequently as a form of functional knowledge representation. Frame and Rules were the next gen
primitive.
2. Meta-Representation - Also known as the issue of reflection in the world of computer science,
meta-representation is known as the capability of formalism to have an information access about
its own state. Smalltalk and CLOS are popular examples of meta-object protocol that not only
provides access to class objects during run time but also redefine the knowledge base structure
during that run time.
3. Incompleteness- There is a demand of traditional logic requirements for additional axioms and
constraints which are mandatory to deal with the real world which the mathematical world
opposes. The area of its usefulness lies in associating the extent of confidence in a statement.
Knowledge representation by Ron Brachman

5. 4 . Definitions and Universals vs. facts and defaults - All the general statements about the universe lie
under Universal like “Humans are not immortal.” When we talk about specific examples of Universals,
we talk about Facts, say, “Albert Einstein was a human and so he was not immortal.” Generally
speaking, definitions and universal seem to quantify the universe whereas facts and defaults are all
about existential quantification.
5. Non- monotonic reasoning – Non-monotonic reasoning can be considered as a type of ideal,
imaginary reasoning.
6. Expressive Adequacy - FOL is something that is quite mostly used even by Brachman and almost all
researchers in order to quantify expressive adequacy. When theoretical limitations are considered, it is
clear enough that FOL, under full implementation is not practical.
7. Reasoning Efficiency - Efficiency basically means ability of a system and thus reasoning efficiency
relates to the run time efficiency of the system. This can be taken into consideration as the rear side of
expressive adequacy. Expressive adequacy is directly proportional to the power of a presentation. But
on the contrary, the effect of automatic reasoning is inversed.
Cont...

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