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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!!