adnan sir ameen

8/8/2019 Adnan Sir Ameen

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ArtificialIntelligence

Submitted to:Sir Ameen A.K Wazir

Submitted by:

Sheikh Adnan Ahmed UsmaniRoll # 36B.S (4 th Year)

Sheikh Zayed Islamic CenterUniversity of Karachi

QUESTION NO.1


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Create and justify your own definition of Artificial Intelligence?

ARTIFICIAL INTELLIGENCE:

Man used his intelligence and tries to transfer his knowledge to the computerfor this purpose he used different ways by using his intelligence and mademachine able to response as human intelligence

OR

The branch of computer science concerned with making computers behavelike human. The term was coined in 1956 by John MC Carthy at theMassachusetts Institute of Technology.

It includes:

Game Playing: Programming computer to play games as a chess andcheckers

Expert System: Programming computers to make decisions in real lifesituations (For e.g. some expert system help (Doctorsdiagnose disease based on symptoms)

Natural Language: Programming computer to understand Natural HumanLanguage.

Neutral Network: Systems that simulate intelligence by attempting toreproduce the type of physical connection that occur inanimal brain.

Robotics: Programming computers to see and hear and react tosensory stimuli.


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QUESTIONS NO.2

Let me say "A time will come when A.I Researchers will be able to provide so much intelligence to machine that it will behave exactly same as human being and will be consider his true copy." Performsome reasoning based on you know about "A.I" and also provide somereasoning in the light of Quran and Sunnah. To verify and to falsify statement.

AI is making computer smarter and more powerful, the dream of building themachine that can fully duplicate the human brain will probably not be realizedin our life time. Despite major advances in all areas of computer science manyquestions whether we will ever be able to create a computer that willaccurately immolate the function of a human mind. Dreyfus and Dreyfus in1988 facts that the public is being misled about AI. Its use fullness is overblown and is goals are impossible. They say we will be never be able toestablish rules for all the ways we think the human mind is just to complex toduplicate. After all, a computer is one processing unit CPU while the humanbeing has over100 billion processing elements.

WITH RESPECT TO THE QURAN AND SUNNAH:

The human brain with its mind and capability of reasoning places man willabove the rest of his creatures Surah Al Baqarah clearly describes the

conversation b/w ALLAH and his angels, at the time of man's creation."And remember when your Lord said to the angels: Verily I am going to

place mankind generation after generation on earth".

They said:Will you place there in those who will make mischief there in and

shed blood, while we glorify you with praises and thanks and sanctify you

He said:He knows that you do not know and He taught Adam all the

names of everything, then he showed them to the angles and said: Tell methe names of these if you are truthful.

They said:Glory is to you we have no knowledge except what you have

taught us verily it is you the All Knower the All Wise.


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He said:O Adam! Inform them of their names. He said: Did I not tell you

that I know the ghaib in the heavens and the earth and I know what you reveal

and what you have been concealing (2:30-33)

Adams ability to learn and understand and remember positions him as asuperior being although animals can also learn think and feel but humans canunderstand and learn from the past and reason himself.

The brains ability to process information is unsurpassed by any othermachines, not even by the latest technology computers etc until now or latereven the computer may work fastly but the brain is much more insight andprudent. The brain unsurprisingly can perform multiple complex tasks at a timelike thinking memorizing, counting, listening, speaking, planning, takingdecisions and last but not the least dealing with emotions an feeling.

Therefore it is almost impossible to build such a machine that worksexactly same as human brains in the later centuries, since the dynamic featureof human brain is mind or aql.


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QUESTION NO.3

Explain how an expertly system can assists religion scholars? Mentionsome of the difficulties than system may face while performing itstask to solve such type of problems that consists uncertainties and vagueness and explain how it can overcome the difficulties using theDempster Shafer Theory of Evidence and fuzzy logic?

Undoubtly an expert system is the best field of A.I that is used to assistsreligious scholars. A.I knowledge engineers can make that type of ExpertSystem which solves all the problems related to Islamic Fiqh. It treats like aFaqih, knowledge Engineer cans all those information regarding the QuranSunnah and fish and also they develop a logical reasoning to give the solutionof the problem. They knowledge engineer must make sure that the computerhas all the knowledge needed to solve a problem related to particular domainproblem.

In most of the real world problems it is observed that the availableknowledge is either incomplete or inexact or vague. Even under theseconditions on expert has to come out with some acceptable solutions of hisproblems and how he can avoid it in future the Aalim then asks hum about theconditions of the problems. The Aalim then asks him about the conditions of the problems. The Aalim then asks him about the conditions of the problems.

The Aalim however may not get the solution under every condition. TheDempster Shafer theory is able to overcome the problems associated withuncertainty.

Let U be the Universal set and A its subset. Let us now define a function m: P(U) [0, 1] which satisfies the following conditions

Here,m=basic probability assignment ranges with 0-1.

An evidence represented but E C U may be considered to the certain if m (E)=1 we know define a function called belief function, belief p (U) [0, 1] as


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Since the sum of all values m (B) is 1, therefore the belief function lies b/w (0,1).

Fuzzy logic was developed to deal with such situation where information

may be somewhat vague. For example in the statement Ali is muttaqi wherethe word muttaqi is fuzzy end is truth value exactly 0 or 1. Here the truth valuecan assume any values in the interval [0, 1]. In can expert system factsrelation judgment opinions contained within the expert knowledge usuallymanifest various degrees of impression and uncertainty.


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QUESTION NO.4

Criticize for computer software being intelligence

TURING TEST The turing test is a test of machines ability to demonstrate intelligence. It

proceeds as follows a human judge engages in the natural languageconversation with one human and one machine each of which tries to appearhuman. All are placed in isolated locations. If the judge cant reliably tell thecomputer machine from the machine, the machine, the machine is said tohave passed the test. It should be limited to a text only channel to test themachines intelligence.

WEAKNESS OF THE TEST The Turing test is based on the assumptions that human beings can

judge a machines intelligence y comparing only behavior and the value of comparing against the human b/c of these and others. Some A.I researchersquestioned about the usefulness of the test. The Turing test does not directlytest whether the computer behaves intelligently it tests only whether thecomputer behaves like a human being since human behavior and intelligencebehavior exactly the same thing, the test to accurately measure intelligentbehavior in two ways.

SOME HUMAN BEHAVIOR IS UNINTELLIGENT The test requires that the machine be able to execute all human

behavior whether they are intelligent or not. It even tests for behavior that wemay not consider intelligent at all. If a machine cannot imitate behavior indetail it fails the test.

SOME INTELLIGENT BEHAVIOR IS IN HUMAN

The Turing test does not test for highly intelligent behavior. If it were tosolve a computational problem that is impossible for any human to solve thenthe interrogator would know the problem is not human and the machine wouldfail the test.


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QUESTION NO.5

What is mean by domain knowledge?

DOMAIN KNOWLEDGE:

It means the content of a particular field of knowledge. It is defined as

The knowledge about solving specific problems is called the domainknowledge.

EXAMPLE

A medical expert system designed to diagnose infection disease will have agreat deal of knowledge about certain symptoms caused by infection diseases.In this case the knowledge domain is medicine and consists of knowledgeabout disease symptoms and treatment.


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QUESTION NO.6

What are the common schemes used to represent knowledge?Describe each, choose and apply one if the scheme check the validity of an argument present in the following paragraph?

KNOWLEDGE REPRESENTS SCHEMES:

Knowledge is a collection of related facts procedures, models, andhevrssties that are used in problem solving or inference system. Onceknowledge it needs to be organized. It can be organized in one or moreschemes or configuration. A variety of knowledge representation scheme has

been developed over the years. These include the production rules inclusionhierarchies, mathematical logic, frames, scripts table, line, trees, semanticnetwork, constraints etc.

REPRESENTATION IN LOGIC

The general form of any logic process is

Input outputPremises logical processinference

Or orFactsconclusion

First information is given statement are made or observations are noted. These form the input to the logical process. These are known asprocesses.

Second the premises are used by the logical process to create the

outputs which contains the conclusion called Inference.

With this process fails that are known to be true are used to drive new factswhich also must be true. The two basic forms of computational logic arepredicate logic and propositional logic.


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PROPOSITIONAL LOGIC

A proposition is a statement that is true or false. In propositional logic weuse symbols like letters of alphabets to represent various propositions can becombined using logical connections by using symbols for various propositionsand relating them with connectives a complete set of premises with resultingconclusions can be expressed.

PREDICATE LOGIC

Propositional logic is not very useful in A.I. A.I uses predicate logic. It ismore sophisticated form of logic that uses all same concepts and rules but inamore finer detail. It is the basis for the AI language called PROLOG. Inpredicate calculus a proposition is divided into two parts, the argument andthe predicate. The arguments are the object about which the assertion is madeand predicate is the assertion made about them.

SEMANTIC NETWORK

It is a knowledge representation method is based on a network structurecomposed of notes and links that show hierarchies relationship b/w objects i.e.quiet, efficient in the sense that each object can be represented once andpointers can be used for cross references rather than naming an object.Explicitly time and again involves in a relation. It is not only efficient in termsof saving space but also searching time is very fast.


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QUESTION NO.7

Describe and discuss the relative advantages and disadvantages of some of the various search techniques. Give an example of a problemfor which you find?

B.F Search works better thean DF search. DF search works better than BF search.

There are several techniques for searching for a possible situation. The mostimportant and common ones are as follows

a. Depth First Searchb. Breadth First Searchc. Hill Climbingd. Least Cost Search

1. DEPTH FIRST SEARCH

In depth first search whenever a choice is given to search from several

nodes, it always prefers to choose the deepest one and the deepest node isone which is farthest from the start node

EXAMPLE: To understand exactly the search worked. Consider the tree inwhich F is the goal.

Depth first search will traverse this graph in the order to AB, DB, EB, and ACF.In this you go left until you reach either a terminal mode or the goal. If youreach a terminal node then you backup one level go right and then go left untilyou encounter either the goal or a terminal node. This process continues untilyou find a goal.


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A depth first search is certain to find the goal b/c as a worst case itgenerates into an exhausted search.

EVALUATION

The depth first search found a fairly good solution on its first try withoutany back tracking which is good. However to arrive at the optimal solution itwould have to traverse nearly all the nodes which is not good. It can be quiet,poor in cases in which you have to explore a particularly long branch only tofind that is no solution at its end. This situation cause a time waste and leadsto breadth first searching

2. BREATH FIRST SEARCH

Breath first search generate all nodes at particular level I before itexplores the nodes of next level (i+1)th level.

Here C is the goal, it visits the node ABC, this search also generates finding asolution if exists b/c it will eventually degenerates into an exhausted search.

EVALUATION

It is easy to find solution at the shortest level. It performs well by findinga solution without back tracking but the disadvantage of the breath first searchis seen when you try to find a goal that is located several layers deep. Here itexpands substantial effort to find it.

3. HILL CLIMBING SEARCH

A search algorithm that attempts to find as a first solution one thatminimize the number of connection will use the heuristics that state the longerdistance covered. The greater the like hood that you will be places closer tothe destination thereby reducing the number of connection in AI. This type of search method is called hill climbing.

EVALUATION


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This is fairly good b/c it tends to reduce the number of nodes that needsto be visited before it reaches the solution however it can suffer three possiblemaladies.FALSE HILL: here the search back tracks extensively to find the solution.PLATEUS: in which the next step look equally good or bad. In this case the hill

climbing is no better than depth first search.RIDGES: hill climbing is not effective in this case b/c the ridges are to becrossed several times during back tracking.

4. THE LEAST COST SEARCH

The opposite of the hill climbing is the least cost search. Apply the least costsearch to the flight scheduling problem implies that the program will take theshortest connectivity flight in all cases so that the route found will have a goodchance of having the shortest distance unlike the hill climbing search whichminimized the no of connection least count search minimized no of milestraveled.

EVALUATION

The least cost search has the same advantages and disadvantages asthe hill climbing search except in the reverse order. There can be false valleylowlands or gorges but overall the least cost search tends to work fairly well.We can only say that on the average it will out perform a blind search

EXAMPLE:

When we find breadth first better then depth first or vice versa:

In the same example given above to reach from New York to LOS ANGLES. Wewill find a different result from different search techniques when we check theresult a/c to shortest distance BREDTH FIRST is best it covers the shortest


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distance of 2600 miles while in order to touch minimize number of node DP|EPTH FIRST is the best b/c it touches only three nodes.

QUESTION NO.8

What is knowledge engineering? Discuss knowledge acquisition withsuitable example?

KNOWLEDGE ENGINEERING:

The process of building an expert system is often called knowledgeengineering. It is highly complexes process. Knowledge engineer acquiresknowledge from the human expert and builds this knowledge into the expert

system it may consist of procedures, strategies and rules to thumb that ahuman expert normally follows

KNOWLEDGE ACQUISITION The knowledge acquired may consist of facts, rules, concept, procedures,

formulas or any other important and useful informations. This knowledge maybe obtained from several sourcesE.g. report, textbook, case studies, the human expert database etc. howeverthe knowledge gathered directly from the human expert may be more close toreality. This is b/c a human expert not only possesses technical knowledge in aparticular problem but also has knowledge about how to effectively andefficiently use this technical knowledge for problem solving.


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QUESTION NO.9

One of the difficulties of vision is that a three dimensional array whendigitized as an image what are some ways in which the depthinformation in the scene can be inferred? Discuss in detail thecommon recognition patterns in vision and pattern recognition?

DETECTING SURFACE DIRECTION:

If a satellite takes a picture of a mountain, how computer woulddetermine whether it is a mountain or a valley? To interpret an image of themountain the computer must know the direction of a surface by studying the

way that it reflects light. A program that analyses the image can be used therelative brightness of the surface to determine whether computer is viewing amountain or a valley. However this is a complex task and becomes overwhitening with complex ones.

DETRMINING SURFACE TEXTURE:

A human being can easily distinguish b/w different things such as glass,ball, iron etc due to surface texture. This again due to the way light reflects onthe thing smooth surface scatters light hence, the relative brightness of arough surface is less then smooth surface. Due to brightness of each objectcomputer can easily determine whether this surface is smooth or rough.

In a real world situation it requires more than simply comparing therelative brightness of object, this because that can object is also affected by itscolors and the reflective qualities of the object. Therefore determine texturerequires two or more image from different viewpoints in relative to the lightsource of the objects. Therefore, the computer can distinguish b/w the texturesby composing the change of the brightness.


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COMMON RECOGNITION PROBLEM

Assuming that you can solve all problems correctly interpreting an image byusing either a two dimensional or three dimensional systems, you still have theproblem of correctly indentifying objects or features that make up the image.

The problem o\is probably the harder one to solve as the next discussions willshow

1- Over Lapping Object

One of the toughest problems that you will encounter when trying tocreate a vision system is the recognition of overlapping objects.

The trouble is not that the computer cannot tell that one object is in frontof another generally shadows and differences in shading supply sufficientclues. The real difficulty is programming the computer to recognizepartial objects for what they are. For example, if you instruct thecomputer that a triangle has three sides and three vertices and if thecomputer sees a triangle. That has a vertex what is obscured by anotherobject (or perhaps that is out of the cameras field of view) how does thecomputer know that it is still seeing a triangle when though the thirdvertex is missing.

There are many approaches to this problem but perhaps the mostinteresting solution band the one closed to the way that the human eyedoes it is called controlled hallucination. In this method the computerguided by the initial information postulates that is seeing a triangle andtries to verify this by some means such as b y computing that the twolines will intersect. Somewhere in the region that is obscured. As you canguess, this is a tracking process in all but highly controlled environments.

2- Recognition Of Object By Classification

Another difficult problem is programming the computer to recognizeclasses of objects that a tree is a tree or that a house is a house. It is fareasier to make the computer recognize a specific objects than it is tomake recognize objects in a certain classification. The reason for this isthat you can give specific objects a strict asset of limityations to whichthey must confirm but you must keep a class definition quite general andloose to cover all slight variances.As of this writing it is not clear how this


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problem will be solved for general cases. Letr as the chapter developssome program that perform pattern recognition you will see that thecomputer can determine simple geometric shapes based upon a classdefinition but that the techniques that can be applied to these types of objects donot translates the highly complex objects.

3- Optical illusions:

The overview of image processing is complex without a brief creatrion of optical illusions an dtheir effect on computerized trhe system currentlymany optical illusions that fool human has effect a computer analysis of same image. For example A and B in given figure are exactly the samelength but A appears to be longer. However a computer would not makethe mistake.


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QUESTION NO.10

What is natural language processing? Use restricted grammar toexplain natural language processing?

NATURAL-LANGUAGE PROCESSING:-

Natural Language processing, usually abbreviated NLP tries to make thecomputer capable of understanding commands written in standard humanlanguage.A Natural Language processor does not care how a sentence is input into thecomputer. Its job is to extract information from that sentence.

RESTRICTING LANGUAGE:-

One of the most difficult aspects of constructing an NLP driven system isthe complexity and flexibility of human language when you implement anatural language processor, it is tempting to try to restrict the type of sentencethat the processor will understand to subset of the natural language. In anycase it is necessary to restrict the grammar that the processor in this chaptercan accept. If this were not done the code to each example would be far toolong. Therefore, for most of the examples in this chapter assume that allsentences are declarative and not interrogative and that they generally follow

the standard from.

Subject, verb, and object:-

It should also assume that all adjectives precede the noun that theymodify.

While all adverb follow the verb that they modify. Finally it should assume that all sentences must end with a period.

Therefore, the following sentence is valid.

The child runs to the house. The larger child runs quickly to the window .However the processor in

this chapter will decide that sentence such as. The child quickly runs to the house are invalid because the adverb

quickly precedes the verb runs.


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FOR EXAMPLE:-

Word TypeDoor NounWindow NounHas VerbRuns VerbLarge adjective

The determiner To Preposition

THE STATE-MACHINE NLP PARSER:-

The state machine parser uses the current state of the sentence topredict what type of word may legally follow. A state machine is a directedgraph that has shows. The valid transitions from the one state to another.

FOR EXAMPLE:-

A simple example by using the serntence. The child runs quickly to the largehouse.This diagram of the sentence verify that it follows the GI grammar.

The child runs quickly to the large house.DET Noun Verb adverb prep det Adj. Noun


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The state machine to become noun. The state machine has now beenstarted. The next word the verb runs. Above figure show you the there are twopossible transitions from a noun to a verb or to place a new verb into statethus the state machine is now at the mod verb.

THE CONTEXT-FREE RECURSIVE-DESCENTS NLP PARSER:-

To understand context free recursive NLP parser one must look at theconstruction of sentence in a completely different way from the way that. Onelooks at they state machine model the rules that govern how each of the pactsmay be constructed are called the production rules of the grammar. A contextfree parser uses there productions rules of the grammar. The right as producesNP stands for noun phrase and VP stands for verb phrase.

Sentence NP+VPNP determiner + nounNP det + adj + nounNP prep + NPVP Verb + NPVP Verb + Adverb + NPVP Verb + AdverbVP Verb

To see how can apply these rules to a sentence, consider this diagram.

A Parser that generates this type of tree is called context free becausethe tree is not based upon the context of each element.

THE NOISE-DISPOSAL PARSER:-


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These types of application only interested in the information that thesentence contain. This idea leads to the variation on the context free parsercalled the noise disposal parser. This type of a parser is actually quite commonin database type application such as command processor.

FOR EXAMPLE:-Consider a database that consists of company names and their

respective stock prices. Assume database will accept queries like

Here the commands must always be present but the other four elements areoptional

QUESTION NO.11


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What is Robotics? Explain Robotics that covers: Robot arms Industrial Robots Autonomous Robot

ROBOTICS:-

The field of knowledge and technique that can be used to create. Whenmost people hear the word robot, the mental response is usually an image of the hardware that makes up the physical being of the robot. Any robot.Industrial as such you must be able to understand a few of them complex.Problem that you will encounter when you attempt to control a robot arm.

For example: When you reach for a glass of water seems to be effortless andwithout though. However it is s complicated takes that requires the coordination of several muscles. Remember that a baby needs several months todo they same thing. They common robot arm is modeled on the human armsmost robot arm are six axis arm between they allow they greeted freedom of movement.

Shows a sketch of a six axis arm. Each axis whish commonly called a jointsoperated by its own separated motor on as is they case of large arms hydraulicof cylinder.Above figure shows a six axis robot arm actually contains tow co ordinateframe of reference. They base and they two piece of they arm from an x y z coordinates system and thy grip allow. Fine movement with in what system.

Therefore reaching any specific point in space regular.

THE INDUSTRIAL ROBOT


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In they field of robotics most effort has been applied to creating andimproving industrial assembly robots. Because these robots are used in acontrolled environment they can be considerable less smart then autonomousrobots. For now and for they forcible future industrial robot can perform onlythose takes that they have been explicitly programmed to do. Robots can be

taught new skills fist they cant be taught by using a teach pedant or secondthey can programmed by using a robotic control Lang.

THE TEACH PENDANT:

The most common method of programming a robot to perform a newtakes is through the use of each pendent .the teach pendent is a rand heldcontrol box that allows an operator to move the various joints of the robots.Although reach manufacture of robots has a slightly different style of teachpendent, all teach pendent are similar to the sketch show below.

The teach pedant is not linked directly to the but rate is linked through therobots main control computer.

ROBOTICS CONTROL LANGUAGE:


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The teach pending is an excellent method for teaching the robots ingletakes such as welding and palletizing .however as the job come morecomputer and extend even syechroziton become more important or if therobots needs to recognize and response differently to many possibleoccurrence the teach preening system quickly become over burdened . It is for

this reason the robotic control language were developed.An orbit control language is a computer language that is designed to control arobot. A robotic control language contains a build in data base that holds serialinformation about each move that the robot will make.

AUTONOMOUS ROBOTS:

An automat robot is much more complex than the industional robot of automats robots is to operate is the uncontrolled environment of the real worldthen it will need various skills that the industrial robot does not required. Themajor roadblock that is preventing the creation of an autonomous robots is aface that program have not yet developed the accessory software techniquesalso a robot of this type will probably required some parsed processing whichis still in its infamy.

QUESTION NO.12


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Explain the component of expert system which are the relativeadvantages and disadvantages of an expert system and humanexpert?

Expert system are composed of two major parts Development environment Consolation environment

DEVELOPMENT ENVIRONMENT: They development environment is used by they expect system builder to

build they couponed and to introduce knowledge into knowledge base.

CONSULTATION ENVIRONMENT:Issued by an expert to obtain expert knowledge and advice. They

following may exists in an expert system

COMPONENT OF EXPERT SYSTEM.

1. Knowledge base:2. Acquistion module3. Inference engine4. Explantory interface5. User

KNOWLEDGE BASE: They knowledge base contains knowledge necessary for understand

formulating and suffering problem. It includes tow Basie element.

ACQUISITION MODULE:Knowledge acquisition module is they accumulation transfer and

transformation of problem solving expertise from some knowledge source to acomputer program for contracting or expending thief knowledge faze. Potentialsource of knowledge include human expert of textbook, database, special

research reports.

INFERENCE ENGINE: They brain of expert system is they influence engine also known as the

control structure or the rule interpreter.


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USER:Expert system contain a language processer for friendly problem

oriented communication between they user and they computer. Thiscommunication ban best be carried out in a naturally language and in samecauses it is supplanted by menus and graphics.

EXPLANATORY INTERFACE:

They ability to take responsibility for conclusion to there sources iscruise both in they transfer of expertise and in problem solving theyexplanatory interface can takes such responsilbity and explain they expertsystem behavior.

Advantageous of of expert system over human expert:

1. Expert system available 24 hours a day. Every day of a year while ahuman expert wants work continuously.

2. Many or number of expert system can create while that are limitednumber of human experts.

3. Computrized expert can be disrupted can never die while human expertdies and takes all of its knowledge with itself.

4. Knowledge of an expert system can be copied and stored easily whilethat of human expert it is not possible.

5. Computerize expert system can never tried and always perform at itspeak but human experts get tired.

6. A new expert system can easily be created though copy past but it takesa long time to become a human expert.

Disadvantages of expert system over human expert:

1. An expert system cant give nay new suggestion that some with thempassage of time but they human expert through continuous study andremains up to date.

2. A single virus can damage the whole expert system but there is noproblem of virus with a human expert

3. An expert system cannot be available every where at any time but ahuman expert ban walk form one place to another to solve they problem

4. An expert system need some accessories with it to keep it charged orsituation one while a human expert need. Nothing with him

QUESTION NO.13


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In your opinion which topic of is the most suitable fro and most applicable in they field of Islamic studies? Explain A.I has many areasof interest of these. There is most common and most important area.

Robotic NLP Searching for solution Pattern recognition Expert system.

We can see some of they application of A.I in the field of Islamic studies.

ROBOTICS: May be helpful by showing the performance of Namaz,Constructing Mosques or Physical help they can provide.

NLP: Can be helpful in the translation of Quran in much language.

SEARCHING: Explanation of Quran, different Hadith from different book of hadith. Etc

PATTERN RECOGNITION: May be helpful to recognize different animal andbirds whether they are harm or hold.

EXPERT SYSTEM: In Islamic studies expert system has provided its servicesin many fields

1. Mufti2. Hafiz e Quran3. Qaree4. Muhaddich5. Aalim

Now, the major work of Islamic studies has been down using expert systemof A.I field. As proof their success you; need only observe the mainlyapplication of expert system. Today in Islamic studies.

From all Islamic studies field of Aalim Human expert are engineered as

A.I expert system, then it will be the most applicable and beneficial forMuslims. This artificial Aalim will not be the natural Aalim but theintelligence will depend upon its knowledge base. More knowledge is addedto the intelligence assistant it acts more like expert. Field of Aalim isselected as the most suitable and the most applicable because Aalim guidesthe Muslim about the manner principles of Islamic correct way of walking inthe path of Islam and all the guidance about the successful life when aperson is successful in here after this is the final destination of all creation.


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Therefore, we select expert system from A.I field of A.I is also useful inIslamic studies but in very limited areas unlike Aalim, the vast field of Islamic studies.

QUESTION NO.14

Describe the sources of Acquisition of general knowledge, Islamicknowledge and Quran Knowledge.?

SOURCES OF GENERAL KNOWLEDGE:


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Books, internet, news paper, magazine, electronic Media, communicationwith different people.

SOURCES OF ISLAMIC KNOWLEDGE:History of Islam, Quran knowledge, Hadith, Fish, Tafseer

QURAN KNOWLEDGE:Quran reviled by Prophet, Tafseer

QUESTION NO.15

Differentiate b/w knowledge acquisition and knowledge?


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Convention System Expert System

1. a conventional program hasa sequence of predefineinstruction for responding toan event

2. Conventional program usesmathematical and staticallymethod to obtain a pricessolution.

3. Conventional system date +algorithm.

4. Effective manipulate of largedata base.

5. execution is done on a stepby

1. An expert system program onthe other hand attempt toreason a response to an eventusing its knowing based andlogistic rules for problemsolving it uses investigative(heuristic) method to obtainsolutions.

2. Expert system = knowledgebase+ rezoning engineeffective manipulation of largeknowledge base.

3. execution is done by usingflouriest and logic

Database Knowledge Base

Knowledge Acquisition:- Knowledge Elicitation:

1. To obtain knowledge and tostructure knowledge iscalled knowledgeacquisition.

2. Obtain knowledge from allsources of knowledge. Thepurpose of knowledgeacquisition is to developeffective knowledge basessystem. It is concerned withthe transfer of knowledgefrom existing sources suchas expert and book ratherthan learning the knowledgefrom experience. Knowledgeacquisition is recognized asthe bottleneck in thedevelopment of knowledgeBased system

1. To obtain knowledge onlyfrom one source (Calledexpert) is known asknowledge Election.

2. Knowledge elicitation is thetransfer and transformationof problem solvingexpertise, and domainknowledge from a sourceinto a program. It meanextraction of knowledgefrom human expert it iscalled the track back of expert system. Knowledgeextracted by an interfilingb/w participant (knowledgeengineer and experts) thegoal is to fin out the reasonbehind and why it is recalledfrom memory.


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1. it is a software program thatis used to create tablesquires and views

2. A collection of dateorganized in such a way that

computer program canquickly selected desire pieceof data is called date bases.

3. S.Q.L server, Access

1. a knowledge base is acollection of any informationmachine readableknowledge base storeknowledge in a computer

readable from usually forthe purpose of havingautomated deductionreasoning applied to them

2. Pro Log.

Traditional System Expert System1. Software that uses general

knowledge to solve theproblems concerned withgeneral routes or program.

2. this system does not explainthe reasons of conclusion

3. it only has general knowledge

1. Software that uses specificknowledge to attain the highlevel performance is anarrow problem area.

2. This system explains thereasons of conclusion indetail.

3. it works a domainknowlwdge

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