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EXPERT SYSTEM
AND DECISION
MAKING
- Parul Jain
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INTRODUCTION
Artificial intelligence-based computerprograms called Expert Systems havereceived a great deal of attention.
They are used in a huge variety of fields
like medicine, mathematics, engineering,computer science and education etc.
An expert system stores the knowledgeof one or more human experts in a
particular field. ES are used for problems for which there
is no single "correct" solution which canbe encoded in a conventional algorithm.
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EXPERT SYSTEM
COMPONENTS The part of the expert system that
stores the knowledge is called the
knowledge base.
The part that holds the specifics of theto-be-solved problem is called the
global database
The part that applies the knowledge tothe problem is called the inference
engine.
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How to build an ES?
A knowledge engineer starts byreading domain-related literature tobecome familiar with the issues and
the terminology. holds extensive interviews with one or
more domain experts to "acquire" theirknowledge.
organizes the results of theseinterviews and translates them intosoftware that a computer can use.
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How to build an ES? (cont)
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CHARACTERSTICS
Operates as an interactive system Tools have ability to filter knowledge
Make logical inferences based on
knowledge storedAbility to Explain Reasoning
Domain-Specific
Applications Cost-effective alternative to Human
Expert
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FEATURES
Goal driven reasoning or backwardchaining
Coping with uncertainty
Data driven reasoning or forwardchaining
Data representation
User interface
Explanations
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EXPERT SYSTEMS ANDARTIFICIAL INTELLIGENCE
AI programs that achieve expert-levelcompetence in solving problems in task areasby bringing to bear a body of knowledgeabout specific tasks are called knowledge-basedorexpert systems.
The area of human intellectual endeavour tobe captured in an expert system is called thetask domain.
Taskrefers to some goal-oriented, problem-
solving activity. Domainrefers to the area within which the
task is being performed.
The Turing Test
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THE WORKING OF ES
Every expertsystem consists of
two principal parts:
the knowledge
base; and the
inference engine.
The knowledge
baseof expertsystems contains
both factual and
heuristic
knowledge.
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The working of ES (cont.)
Factual knowledgeis that knowledge
that is widely shared found in
textbooks or journals, and agreedupon by those knowledgeable in the
particular field.
Heuristic knowledgeis the lessrigorous, more experiential, more
judgmental knowledge of
performance.
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KNOWLEDGEREPRESENTATION
Knowledge representation formalizes andorganizes the knowledge.
One representation is a ruleconsisting of an IF partand a THEN part.
Another representation, called the unitis based
upon a more passive view of knowledge. The problem-solving modelcontrols the steps
taken to solve the problem. forward chaining -If the chaining starts from a set of
conditions and moves toward some conclusion, the
method. backward chaining -If the conclusion is known but the path
to that conclusion is not known, then that is reasoningbackwards.
The more knowledge a system is given, the morecompetent it becomes.
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RULE BASED ES
Any rule consists of two parts: the IF
part, called the antecedent(condition)
and the THEN part called the
consequent(action).
IF antecedent
THEN consequent
The antecedent of a rule incorporates
two parts: an objectand its value.
A rule can have multiple antecedents
joined by the keywords AND or OR.
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INFERENCE ENGINE
The inference engine is the genericcontrol mechanism that applies the
knowledge present in the knowledge
base to the task-specific data to arrive atsome conclusion.
inference mechanisms that search
through the database and deduce results
in an organized manner:
Forward chaining
Backward chaining
Tree searches
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FORWARD AND BACKWARDCHAINING
Forward chaining - one proceeds froma given situation toward a desired goal,adding new assertions along the way.
Backward chaining - In this strategy,
one starts with the desired goal, andthen attempts to find evidence forproving the goal.
Eg. Rule 1: IF A and C THEN F
Rule 2: IF A and E THEN GRule 3: IF B THEN ERule 4: IF G THEN D
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TREE SEARCHES
A knowledge base can usually berepresented as a branching network ortree.
Two approaches: depth-first search. breadth-first search.
The depth-first search algorithm begins at anode that either represents the given data
(forward chaining) or the desired goal(backward chaining).
Breadth-first search starts by expanding all thenodes one level below the first node. Then itsystematically expands each of these nodes till
a solution is reached or the tree is completelyexpanded.
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Tree searches (cont.)
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INTELLIGENT EDITORS
An intelligent editor acts as an interfacebetween a domain expert and an ExpertSystem.
The editor has direct access to theknowledge in the Expert System and knows
the structure of that knowledge Through the editors, an expert can create,
modify and delete rules without knowledgeof the internal structure of the rules
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ADVANTAGES OF EXPERTSYSTEMS
Permanence
human experts may forget. Reproducibility many copies. Efficiency increased system output. Consistency similar transactions give
same output. Documentation permanent
documentation. Completeness all transactions can be
viewed. Timeliness Entry barriers for competitors. Differentiation
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DISADVANTAGES
Common sense
Creativity in unusual situations.
Learning
no adaptability.
Sensory Experience
Degradation not good when noanswer exists.
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APPLICATIONS
Diagnosis and Troubleshooting ofDevices and Systems of All Kinds. Eg5GL DOCTOR
Planning and Scheduling. Eg GATES
Configuration of ManufacturedObjects from Subassemblies.
Financial Decision Making. EgINSPECTOR
Knowledge Publishing Process Monitoring and Control Design and Manufacturing. Eg
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CONCLUSION
Problem solving is accomplished byapplying specific knowledge rather than
specific technique. This is a key idea in
expert systems technology.
It reflects the belief that human experts do
not process their knowledge differently from
others, but they do possess different
knowledge. With this philosophy, when onefinds that their expert system does not
produce the desired results, work begins to
expand the knowledge base, not to
reprogram the procedures.
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THANK YOU