anusree kbs

7/28/2019 Anusree Kbs

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Knowledge-basedsystems

Presented by:

Anusree S. Nair

Roll no. 9


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3

Components of KBS

Knowledge

base

Inference

engine

User interface

Explanation

and

reasoning

Self-

learning

Figure 1.10: General structure of KBS

Enriches thesystem withself-learningcapabilities

Providesexplanation and

reasoning

facilities

Knowledge base is a repository of domainknowledge and metaknowledge.

Inference engine is a software program thatinfers the knowledge available in the

knowledge base.

Friendly

interface tousers workingin their native

language


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Introduction

Main Components of an KBS

U

serInterfac

e

Knowledge Base

Inference Engine

Expertise

Expertise

Facts / Information

User

Developer


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Knowledge-based systems

Knowledge based systems are artificial intelligent tools working in anarrow domain to provide intelligent decisions with justification.

Knowledge is acquired and represented using various knowledge

representation techniques rules, frames and scripts. The basic

advantages offered by such system are documentation of knowledge,

intelligent decision support, self learning, reasoning and explanation.


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Artificial Intelligence

Artificial intelligence (AI) is the intelligence of machines and

robots and the branch of computer science that aims to create

it. John McCarthy, who coined the term in 1955, defines it as

"the science and engineering of making intelligent machines. It

can also be defined as "the study and design of intelligentagents" where an intelligent agent is a system that perceives its

environment and takes actions that maximize its chances of

success.


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Structure and characteristics

KBSs are computer systems

contain stored knowledge

solve problems like humans would

KBSs are AI programs with program structure of new type knowledge-base (rules, facts, meta-knowledge)

inference engine (reasoning and search strategy for solution, other

services)

characteristics of KBSs:

intelligent information processing systems

representation of domain of interest symbolic representation

problem solving by symbol-manipulation

symbolic programs


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General Concepts and

Characteristics of ES

knowledge acquisition

transfer of knowledge from humans to computers

sometimes knowledge can be acquired directly from the

environment

machine learning

knowledge representation

suitable for storing and processing knowledge in computers

inference

mechanism that allows the generation of new conclusions from

existing knowledge in a computer

explanation

illustrates to the user how and why a particular solution was

generated


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Structure and characteristics

AI programs:

intelligent problem solving tools

KBSs

AI programs with special program

structure separated knowledge base ESs

KBSs applied in a specific narrow field

AI programs

Knowledge-based systems

Expert systems


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Advantages of KBSs

field of interest changes are well-tracked

increase expert ability and efficiency

preserve know-how

can be developed systems unrealizabled with tradicionaltechnology

self-consistents in advising, equable in performance

are available permanently

able to work even with partial, non-complete data


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Disadvantages of KBSs

their knowledge is from a narrow field, dont know the

limits

the answers are not always correct (advices have to be

analysed!) dont have common sence (greatest restriction) all of

the self-evident checking have to be defined

(many exceptions increase the size of KB and the

running time)


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Base techniques of KBSs


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Techniques of KBSs

Based on the knowledge-representation methods and

reasoning strategies applied in the implementation

rule-based techniques

inductive techniques hybrid techniques

symbol-manipulation techniques

case-based techniques

(qualitative techniques, model-based techniques, temporal

reasoning techniques, neural networks)


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KBS is currently used in applications ranging from:

commercial banking systems for processing loan

applications,journey planners and timetable schedulersfor travel firms to visual units used in robotics in the

manufacturing sectors of industry.

Other research areas include : Manufacturing systems

which help in the total manufacturing process from

design through to development. Speech recognition

systems which turn human speech to text of whichprototypes developed so far work in a limited capacity.


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THANK YOU!!

anusree kbs

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