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My today paper 22/08/2014 08:00am

Total marks 80

Mcqs = 40

5 mrks Q = 4

3 mrks Q = 4

2 marks Q = 4

(5 marks Questions)

1. Application areas of fuzzy system. (page 153)2. Elaborate Action predicates in SRTIPS. (page1983. Elaborate ID3 algorithm (page1774. General stages of expert system (page129

(3 marks Questions)

1. Which sub-field of AI is concerned about enabling machine to see, perceive and understand? Briefly explain. (page203

2. Briefly explain Law of Excluded Middle. (page1453. Main phase of linear sequence. (page1294. Which is best term suited for situation in which data in a problem can be separated

into their respective classes by using single straight line. Also give example. (page184, 185

(2 marks Questions)

1. What do you know about the term STRIPS. (page1972. Elaborate the term Genetic Algorithm. (page773. Which topic in AI deal with the concept of partial truth and member function.

(page1474. Out of the training and validation, which term is best suited for situation in which we

give different training examples of correct behavior to machine and then train that machine on these training examples in order to make that machine to learn.

Best of luck

Plz post ur current paper here

And remember me in ur prayers.

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cs607

FIS(Fuzzy inference system) kahan kahan use hoti ha (page153Computer and insan main kn best ha table bna k likhna tha (page182

Unsupervised learning brief (page190Agr instance space increase ho gi to kia concept space increase ho gi? (page167

AI ki wo kn si field ha jo computer ko insan jesa sochny jesa bnati ha (page203

Clips main father n son ka relationship show and assert kraen (page134

Deductive learning with example (page162Group with out labels kia hota ha Mid term k mcqs prh k jaen

AI main kia kia 0 to 1 k drmian ha which terms u have studied (ans probability, Entropy, etc

Aisi problems jo single line se separate na ho .... unhaen kn separate nai kr skta ik example b daen

Degree of truth of fuzy logic kes sy show hota (page147

finalterm paper cs607 23 august compare biological neural network with computer detail ...5 (page182class set is container which doesnot wholy includ or exclude ...agree or not justify... (page145what is machine learing ...3wht u study about computer vision....5 (page203clips stand for ....mcq (page133fuzzy has nature ....mcq

mine todays paper..These are some questions which I remember till now..

what is concept space and instance space? (page166, 167

describe fuzzy logic and crisp function in terms of membership. (page147

briefly describe law of excluded middle (page145

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what do you study in computer vision? (page203

one question was of CLIPS already shared by Asif (MCS 4th). (page133

applications of fuzzy logic? (page147

briefly describe action predicate? (page198

two main types of problems and their subtypes. (page165

My today papers 26-08-14

1. How Machine learning help in developing expert systems (5marks) (page163

2. Action Predicates in STRIPS with example (5 marks) (page198

3. Five parts of the fuzzy inference process (5 marks) (page154

4. Write name of five applications in which we apply learning algorithms. (5 marks) (page163

5. Name of design phase in which ANNs start learning (3marks) (page188

6. Advantages of ANNs (3marks) (page187

7. Defuzzification --> Rule evaluation ---> Fuzzification is a sequence of steps to design fuzy logic machine. Are you agree with the statement also give correct statement (3marks) (page154

8. Names of emergent fields in which learning algorithms are used. (3 marks) (page163

9. Which step of FIS resolve all antecedent statement to a degree of membership between 0 and 1. (2 marks) (page147

10. Knowledge elicitation and its methods (2 marks) (page130

11 Clustering defination (2 marks) (page205

12 Information gain defination (2 marks) (page177

According to my point of view Question no 3 and Question no 7 have same answer which is

• Fuzzification of the input variables• Application of fuzzy operator in the antecedent (premises)• Implication from antecedent to consequent• Aggregation of consequents across the rules• Defuzzification of output

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Similarly Question no 4 and Question no 8 have same answer which is

• Spoken digits and word recognition• Handwriting recognition• Driving autonomous vehicles• Path finders• Intelligent homes• Intrusion detectors• Intelligent refrigerators, tvs, vacuum cleaners• Computer games• Humanoid robotics

But please verify it

Totally from Moaaz file MCQS half were new and half from past papers

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CS607 Final term Paper August 22, 2014

Total 1 Mark MCQ = 40Total 2 Marks Short Questions = 4Total 3 Marks Short Questions = 4Total 5 Marks Long Questions = 4

Some Objective

A single layer perceptron cannot perform pattern classification on linearly separable patterns.►True

►False (Page 186)__________ is the process by which the fuzzy sets that represent the outputs of each rule are combined into asingle fuzzy set.►Aggregation (Page 157)►Fuzzification

►Implication

►None of the given

The tractable problems are further divided into structured and ________ problems►Non-structured

►Complex (Page 166)►Simple

A proposition is the statement of a ________.►Fact (Page 98)►Equation

►Action

►Theorem

The Candidate-Elimination algorithm represents the ____________►Version space (Page 173)►Solution space

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►Elimination space

►None of the given

Identify the step involved in planning phase.

1. Knowledge acquisition from expert2. Coding

3. Resource allocation (Page 129)4. Identify concrete knowledge element

MCq’s where easy mostly from moaaz file and some were from other files tooSubjective

1) What is the law of ‘Excluded Middle’? (2)Answer:-It was Aristotle who came up with the ‘Law ofthe Excluded Middle’, which states that any element X, must be either in set A or in set not-A. It cannot be in both. And these two sets, set A and set not-A should contain the entire universe between them.

2) What is state? (2)Answer:State is a conjunction of predicates represented inwell-known form, for example,

a state where we are at the hotel and do not have either cash or radio is

represented as,

at(hotel) ∧ ¬have(cash) ∧ ¬have(radio)

3) Design phases of ANNs?? (5)Answer:Design phases of ANNs

Feature RepresentationThe number of features are determined using no of inputs for the Problem. These large feature spaces make algorithms run slower. They also make the training process longer. The solution lies in finding a smaller feature space which is the subset of existing features.

Feature Space should show discrimination between classes of the data. Patient’s height is not a useful feature for classifying whether he is sick or healthy .

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TrainingTraining is either supervised or unsupervised.

Remember when we said:

We assume that the concept lies in the hypothesis space. So we search for a hypothesis belonging to this hypothesis space that best fits the training examples, such that the

output given by the hypothesis is same as the true output of concept

Finding the right hypothesis is the goal of the training session. So neural networks are doing function approximation, and training stops when it has found the

closest possible function that gives the minimum error on all the instances

Training is the heart of learning, in which finding the best hypothesis that covers most of the examples is the objective. Learning is simply done through adjusting the weights of the network

Similarity MeasurementA measure to tell the difference between the actual output of the network while training and the desired labeled output The most common technique for measuring the total error in each iteration of the neural network (epoch) is Mean Squared Error (MSE).

ValidationDuring training, training data is divided into k data sets; k-1 sets are used for training, and the remaining data set is used for cross validation. This ensures better results, and avoids over-fitting.

Stopping CriteriaDone through MSE. We define a low threshold usually 0.01, which if reached stops the training data. Another stopping criterion is the number of epochs, which defines how many maximum times the data can be presented to the network for learning.

Application TestingA network is said to generalize well when the input-output relationship computed by the network is correct (or nearly so) for input-output pattern (test data) never used in creating and training the network.

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4) What are action predicates? Also give some examples (5)Answer:Action is a predicate used to change states. It has three components namely, the

predicate itself, the pre-condition, and post-condition predicates. For example,

the action to buy something item can be represented as,

Action:

buy(X)

Pre-conditions:

at(Place) ∧sells(Place, X)

Post-conditions/Effect:

have(X)

What this example action says is that to buy any item ‘X’, you have to be (preconditions) at a place ‘Place’ where ‘X’ is sold. And when you apply this operator

i.e. buy ‘X’, then the consequence would be that you have item ‘X’ (postconditions).

5) Application of Fuzzy inference system (5)Answer:- Page :153Fuzzy inference systems have been successfully applied in fields such as

automatic control, data classification, decision analysis, expert systems, and

computer vision.

6) What is FIS system ? (5)Answer:- Page :153Fuzzy inference system (FIS) is the process of formulating the mapping from a given input to an output using fuzzy logic. This mapping then provides a basis from which decisions can be made, or patterns discerned Fuzzy inference systems have been successfully applied in fields such as automatic control, data classification, decision analysis, expert systems, and

computer vision. Because of its multidisciplinary nature, fuzzy inference systems are associated with a number of names, such as fuzzy-rule-based systems, fuzzy expert

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systems, fuzzy modeling, fuzzy associative memory, fuzzy logic controllers, and simply (and ambiguously !!) fuzzy systems. Since the terms used to describe the various parts of the fuzzy inference process are far from standard, we will try to be as clear as possible about the different terms introduced in this section.

7) Find out the value of following logical operators using Fuzzy-And. (3)Answer:A table of values was given like.

Read the following link to find out more about min(A and B) and max(A OR B).

A B A and-fuzzy B0.7 0.3 0.3

0 0.4 0

1 1.2 1

8) Which term is best suited for the situation where we have combination of disjunction and conjunction? (3)Answer: Page : 176Decision trees give us disjunctions of conjunctions, that is, they have the form:

(A AND B) OR (C AND D)

In tree representation, this would translate into:

9) What is ID3 and how it works?? (3)Answer: Page : 177ID stands for interactive dichotomizer. This was the 3rd revision of the algorithm

which got wide acclaims. The first step of ID3 is to find the root node. It uses a special function GAIN, to evaluate the gain information of each attribute. For example if there are 3 instances, it will calculate the gain information for each. Whichever attribute has the maximum gain information, becomes the root node. The rest of the attributes then fight for the next slots.

10) At which phase in ANNs design system starts learning? (3)Answer:Training

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https://www.calvin.edu/~pribeiro/othrlnks/Fuzzy/fuzzyops.htm


Training is either supervised or unsupervised.

Remember when we said:

We assume that the concept lies in the hypothesis space. So we search for a hypothesis belonging to this hypothesis space that best fits the training examples, such that the

output given by the hypothesis is same as the true output of concept

Finding the right hypothesis is the goal of the training session. So neural networks are doing function approximation, and training stops when it has found the

closest possible function that gives the minimum error on all the instances

Training is the heart of learning, in which finding the best hypothesis that covers most of the examples is the objective. Learning is simply done through adjusting the weights of the network

11) What are the steps of linear model of ES? (2)Answer: Page: 129A linear sequence of steps is applied repeatedly in an iterative fashion to develop the ES. The main phases of the linear sequence are

• Planning

• Knowledge acquisition and analysis

• Knowledge design

• Code

• Knowledge verification

• System evaluation

12) Single layer perception (2)Answer: page 184A single layer perception can perform pattern classification only on linearly

separable patterns, regardless of the type of non-linearity (hard limiter, signoidal).

itnaaaaaaaaa mushkil, so conceptual

puri book ko chaan chaan k mer gai but phir b subjective nai ata tha, pta hi nai chala k kia or kidher sy aya

well, jo yad ha wo post ker rhi hun bas dua karna k papers achy ho jaen.

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Write down the names of some areas where clustering is benifitial.

How mechanical intelligence impact the Robot.

how ANNs manages their w8s.

Disjunctive space

FindS algorithm

compare different searches each other and which is best.

define domain of problem.

Version space and ID3 are connected with each other, agree or not, give solid reasons.

salam to all

MCQS 40

4 QUIZ OF 2 MARKS

4 QUIZ OF 3 MARKS

4 QUIZ OF 5 MARKS

objective mostly past papers but statements change.

or subjective last walya 3 chapters sa tha.

about machine learning NEURAL NETWORK k 3 sa 4 quiz thya or mcqs b thya. 3 sa 4 quiz ma senrio given tha or batna tha kon sa alogrithme batter h aink liya. quiz about Rules quiz about ESDLC quiz about learning agent or algoritm

MCQZ k liya mozz file dakh lain .

TOTAL MCQS 40

35 MCQS WAS MOAZ FILE

1. un-supervised learning2. inductive learning3. write the name of predicate action?4. what is STRIPS?5. comparison b/t brain and computer?

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6. Elaborate the five parts of fuzzy infrence system?7. Write the main phases of linear sequance of ESDLC?8. Patteren recognition in computer vision?9. backword chain steps define?

un-supervised learning

Clustering is a form of unsupervised learning, in which the training data isavailable but without the classification information or class labels. The task ofclustering is to identify and group similar individual data elements based on somemeasure of similarity.write the name of predicate action?

the predicate itself, the pre-condition, and post-condition predicates.

what is STRIPS?

STRIP is one of the founding languages developed particularly for planning. Let us understand planning to a better level by seeing what a planning language can represent.

comparison b/t brain and computer?

Elaborate the five parts of fuzzy inference system?

Five parts of the fuzzy inference process• Fuzzification of the input variables• Application of fuzzy operator in the antecedent (premises)• Implication from antecedent to consequent• Aggregation of consequents across the rules• Defuzzification of outputWrite the main phases of linear sequance of ESDLC?

The main phases of thelinear sequence are

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� Planning� Knowledge acquisition and analysis� Knowledge design� Code� Knowledge verification� System evaluationPattern recognition in computer vision?

Computer vision encompases topics from pattern recognition, machine learning,geometry, image processing, artificial intelligence, linear algebra and othersubjects.

backword chain steps define?

1. Start with the goal.2. Goal may be in WM initially, so check and you are done if found!3. If not, then search for goal in the THEN part of the rules (matchconclusions, rather than premises). This type of rule is called goal rule.4. Check to see if the goal rule’s premises are listed in the working memory.5. Premises not listed become sub-goals to prove.6. Process continues in a recursive fashion until a premise is found that isnot supported by a rule, i.e. a premise is called a primitive, if it cannot beconcluded by any rule7. When a primitive is found, ask user for information about it. Back track anduse this information to prove sub-goals and subsequently the goal.

Mcqz form clips and fuzzi systems mostly

(1)What is Goal in STRIPS given an example 2marks

GoalGoal is also represented in the same manner as a state. For example, if the goalof a planning problem is to be at the hotel with radio, it is represented as,at(hotel) _ have(radio)(2) elaborate the inductive learning 2mrks

Inductive learningInductive learning takes examples and generalizes rather than starting with existing knowledge.

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(3) Boolean logic is a subset of fuzzi logic if u agree give reason?

Fuzzy logic is a superset of conventional (Boolean) logic that has been extended to handle the concept of partial truth -- truth values between "completely true" and "completely false".(4) ESDLC steps?

• Feasibility study • Rapid prototyping • Alpha system (in-house verification) • Beta system (tested by users) • Maintenance and evolution

(5) write 3 phases of ES life cycle

Genetic Algorithm is inspired by the structure and/or functional aspects of the biological neural networks and it consist of an interconnected group of artificial neurons. Do you agree or not? 5 marks(7) advantages of neural network?

• Excellent for pattern recognition• Excellent classifiers• Handles noisy data well • Good for generalization

Who does neural network resemble the human brain.It resembles the brain in two respects:� Knowledge is acquired by the network through a learning process (calledtraining)� Interneuron connection strengths known as synaptic weights are used tostore the knowledge

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(9)Elaborate version space ?

Version space is a set of all the hypotheses that are consistent with all thetraining examples. When we are given a set of training examples D, it is possiblethat there might be more than one hypotheses from the hypothesis space that areconsistent with all the training examples.(10)generic algorithm inspired by the and/or structure of biological neural networks

Ifu r agree give reason 5 mrk

Elaborate the 2 main branches of space but I forget the name of space ma be hypothesis space or version space I don’t knw 5 mrks

CS604 current Final term paper 1-3-2014

MCQs half were new and half were old!

Q1) What is Goal in Strips? Give an example. (2 Marks)Goal is also represented in the same manner as a state. For example, if the goal of a planning problem is to be at the hotel with radio, it is represented as,at(hotel) ^ have(radio)Q2) Write two fields or data types of CLIPS? (2 Marks)Fields are the main types of fields/tokens that can be used with clips. They can be:1. Numeric fields: consist of sign, value and exponent• Float .e.g. 3.5e-10• Integer e.g. -1 , 32. Symbol: ASCII characters, ends with delimiter. e.g. family3. String: Begins and ends with double quotation marks, “Ali is Ahmed’s brother”

Q3) What is Knowledge elicitation? (2 Marks)Getting knowledge from the expert is called knowledge elicitation vs. the broader term knowledge acquisition. Q4) What do you know about Training Process? (2 Marks)Ans:Real learning involves some generalization from past experience and usually some coding of memories into a more compact form. Achieving this generalization needs some form of reasoning.

Q5) Who does neural network resemble the human brain. (3 Marks)Ans:It resembles the brain in two respects:

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• Knowledge is acquired by the network through a learning process (called training).• Interneuron connection strengths known as synaptic weights are used to store the knowledge.

Q6) Write down fuzzy statement in everyday life. Elaborate and give reason. (3 Marks)

Q7) Write 3 advantages of Artificial Neural Networks. (3 Marks)Ans:Advantages of Artificial Neural Networks:Excellent for pattern recognitionExcellent classifiersHandles noisy data wellGood for generalizationQ8) How decision tree and candidate elimination algorithm work with disjunctions of conjunctions,? (3 Marks)

Q9) Discuss ID3 in decision tree representation? (5marks)Ans:ID stands for interactive dichotomizer. The first step of ID3 is to find the root node. It uses a special function GAIN, to evaluate the gain information of each attribute. For example if there are 3 instances, it will calculate the gain information for each. Whichever attribute has the maximum gain information, becomes the root node. The rest of the attributes then fight for the next slots.

Q10) “Planning predicate is a predicate that define states and condition is a predicate that is used to change states”. Do you agree with the statement or not? (5 Marks)

Q11) (P→Q) ^ ¬ (P ^ (Q ^ ¬R)) Convert into Conjunctive Normal Form (CNF)? (5 Marks)Ans: (¬ P v Q) ^ (¬ P v (¬ Q v R))---------final form

Q12) Five parts of fuzzy inference process? (5 Marks)Five parts of the fuzzy inference process• Fuzzification of the input variables• Application of fuzzy operator in the antecedent (premises)• Implication from antecedent to consequent• Aggregation of consequents across the rules• Defuzzification of output

Stay Blessed remember me in ur prayers!

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VU Today's Final Term Paper For Fall 2013Total Questions = 52 of Total 80 MarksTotal MCQ = 40 Each of 1 marksTotal Short Questions = 4 Each of 2 marksTotal Short Questions = 4 Each of 3 marksTotal Long Questions = 4 Each of 5 marksQ1: difference between ambiguous and unambiguous problems? 2Q2: how can u elaborate the need of validation during training ?? 2Q3: which term is best suited for a situation in which we give a set of example of input/output pairs to find out a rule that does good job of predicting the out associated with a new input ? 2Q4: which term is best suited for a situation in which we try to find out a relationship between input and output of a function (concept) ? 2Q5:which term is best suited for a person who has specialized knowledge, skill and experience in specific area? give an example form daily life ? 3Q6:which term is best suited for a situation in which data problem can not be separated into their respective classes by using a simple line? give an example 3Q6:write name of some emergent fields in which machine learning algorithms are being used ? 3 Q7: write down the task/application for which "connectionist" approach is well suited? 5Q8:how can u elaborate the functioning of unsupervised methodology in neural network? 5Q9: do you think machine learning helps human being? justified ur answer with solid reasons ? 5Q10: out of different design phase of ANN which design phase is best suited for a situation in which training data is divided in to k sets , k-1 sets are used for training and remaining data set is used to ensure better result and to avoid over fitting ? 5VU Current Final Term PaperSemester Fall 2013Total Questions = 52 Total Marks = 80Total 1 Mark MCQ = 40Total 2 Marks Short Questions = 4

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Total 3 Marks Short Questions = 4Total 5 Marks Long Questions = 4

What is Goal in STRIP?Define Version Space?Which term best suites for the statement: “There is a whole class of problems; we represent them in the input space and we could classify them using a straight line.”Why Genetic algorithm is used in the biological theory of Human evolution? Also write its functions.Define fuzzy inference process. Describe the five parts of fuzzy inference process? Which term best suites for the: “is a subfield of Artificial Intelligence and study algorithms, techniques and applications that help us make machines that can "understand" images and videos.”

aoa friends

my paper of cs607 was easy.

there were 52 total questions

Total 1 Mark MCQ = 40Total 2 Marks Short Questions = 4Total 3 Marks Short Questions = 4Total 5 Marks Long Questions = 4

1. write add command in CLIPS to add 3 and 4. 2marks2. elaborate planning. 2marks3. difference between fuzzy values and crisp values.2marks4. write three advantages of ANNs.3marks5. write general steps of expert system life cycle.5marks6. genetic algorithm structure is inspired from ANNs. do u agree or not with this statement? give reason to support your answer. 5marks7. write parts of fuzzy inference process 5 marksmcqs mostly from moaaz bhai file.

if any one have answers or some idea of these qustions then plz reply.

Thanks

Q.Write down the names of some areas where clustering is benifitial?

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Q.How mechanical intelligence impact the Robot?

Q.how ANNs manages their w8s?

my paper50% mcq from maz file new are from breth first search and coceptual and easy

objectone satement the is ka bata na tha za konse type ka knowlegge ha wo meta knowledge ke type theadvantage of nural networkmean square errorcheracterstics of lunrnning . distance measures . feacture reperstion . of genralizationin q unsupervised luraning ka thaconcep space or intance space ka differance thabest of luck gayspaper bhoooooooooot muskil takch mcq yad ha ju ye taMCQs:1.Softcomputing naturally -----learning2.which on is not a manaing part-----3.motation is small random -----4.deductive learnin----5.inductive learning----6.medical imaging is field-----7.which is not belong unsupervised SOM--ART--8. which on iis not benefit of ANN----Good for generalization9.The brain is a collection of about 100 billion interconnected neurons10.measure of the effectiveness is------11. popular defuzzification method is the centroid calculation12.tester is called----13.FIS is ....control systm14 boolean is subset of .....15 before agreegation wich process is--------implication16.Usually a triangular graph is chosen to represent a fuzzy set, w 17. which command is used for remove all rules in clips

bs itnay mcq yad ta kch mcqs Expert system sa aur Moaz ke file sa ta

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plz anyone explian these

difference between ambiguous and unambiguous problems

how can u elaborate the functioning of unsupervised methodology in neural networkWhy Genetic algorithm is used in the biological theory of Human evolution? Also write its functions.

Q: Write down the names of some areas where clustering is beneficial.

Ans: informativeness and coherence

40 MCQ's...25-30 MCQ's from MOAAZ file but MCQ's mai blanks change thi, i means Moaz file MCQ's mai jo blank hai wo sir ne given kr diya tha aur jo given hai usay blank kr diy tha es liye read complete MCQ's sentence carefully.Short QUestion:2 marks k all Question mai just ye btana tha k es mai best suitable term kn si hai. like:Q: which term is best suited for a situation in which we give a set of example of input/output pairs to find out a rule that does good job of predicting the out associated with a new input ? 2Q: which term is best suited for a situation in which we try to find out a relationship between input and output of a function (concept) ? 2Q:which term is best suited for a person who has specialized knowledge, skill and experience in specific area? give an example form daily life ?Q: which term is best suited for a situation in which data problem can not be separated into their respective classes by using a simple line?2Q:write three advantages of ANNs.3marksQ: 0.0 and 1.0 ka btana tha like truthness and flaseness, membership function best term mai aaya tha 3Q: comparison b/t brain and computer? 3Q: Elaborate the five parts of fuzzy inference system? 5

Q: do you think machine learning helps human being? justified ur answer with solid reasons ? 5

Q: aik 5 marks ka qquestion tha Robot k baare mai likhna tha 5

which term is best suited for a situation in which we try to find out a relationship

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between input and output of a function (concept) ?ans:

Application TestinG

plz tell me answer of these questions

Q: which term is best suited for a situation in which we give a set of example of input/output pairs to find out a rule that does good job of predicting the out associated with a new input ? 2

Q:which term is best suited for a person who has specialized knowledge, skill and experience in specific area? give an example form daily life ?Q: which term is best suited for a situation in which data problem can not be separated into their respective classes by using a simple line?2

My todays cs607 final paperObjective:

1. FIND-S finds the maximally specific hypothesis possible within the version space2. Learning problem is primarily composed of three things.3. Deductive learning working on existing facts and knowledge4. In Unsupervised search Given a set of examples with no labeling, group them into sets

called clusters5. A concept is the representation of the problem with respect to the given

Attributes1. Soft-computing is naturally applied in machine learning applications.2. Genetic algorithms have been employed in finding the optimal initial weights of

neural networks.3. Fact list using command4. Clips , anything after a semicolon is a comment5. Inference networks encode the knowledge of rules and strategies.6. Fuzzy sets, unlike classical sets, do not restrict themselves to something lying wholly

in either set A or in set not-A.7. The degree of truth that we have been talking about, is specifically driven out by a

function called the membership function.8. Output of learning problem in which phase.

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a) Training:

b) Validation

c) Application

d) None of the given1. The Candidate-Elimination algorithm represents the version space by storing only its

most general members (denoted by G) and its most specific members (denoted by S). Given only these two sets S and G,

2. Drawback of FIND-S, that, it assumes the consistency within the training set.3. A linear sequence of steps is applied repeatedly in an iterative fashion to develop the

ES.4. Predicate logic and the classical and successful expert systems were limited in that

they could only deal with perfect boolean logic alone.5. Earlier expert system was known as

a) Agent

b) Theorem

1. Computer vision extracts useful information from static pictures and sequence of images.

2. A planning system can avoid any action that is just not possible at a particular state.

Subjective:

1. Different technologies like fuzzy logic, GA, ANN. Best suited term?2. Fuzzy logic deals with reasoning. Which is fixed n not partial true? Justify yes or no.3. Probability and fuzzy logics are same term? Justify your answer’4. In neural network, Some weak signal combined into one strong signal. Name best

suited term.5. For robot which condition is difficult to handle. Ans: Deal with unexpected situation

Q3: which term is best suited for a situation in which we give a set of example of input/output pairs to find out a rule that does good job of predicting the out associated with a new input ? 2

Application Testing

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• A network is said to generalize well when the input-output relationship computed by the network is correct (ornearly so) for input-output pattern (test data) never used in creating and training the network.

Q: which term is best suited for a situation in which we give a set of example of input/output pairs to find out a rule that does good job of predicting the out associated with a new input ? 2

SupervisedGiven a set of example input/output pairs, find a rule that does agood job of predicting the output associated with a new input.

Q5:which term is best suited for a person who has specialized knowledge, skill and experience in specific area? give an example form daily life ? 3marks

Expert system

Before we attempt to define an expert system, we have look at what we take the

term ‘expert’ to mean when we refer to human experts. Some traits that

characterize experts are:

• They possess specialized knowledge in a certain area

• They possess experience in the given area

• They can provide, upon elicitation, an explanation of their decisions

• The have a skill set that enables them to translate the specialized

knowledge gained through experience into solutions.Try to think of the various traits you associate with experts you might know, e.g. skin specialist, heart specialist, car mechanic, architect, software designer. You will see that the underlying common factors are similar to those outlined above.

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