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Artificial Intelligence Question Bank - Write Answers Here!

Discussion in 'Computer Science | IT | Networking' started by Ankita Katdare, Jul 14, 2011.

  1. Ankita Katdare

    Ankita Katdare Moderator

    Engineering Discipline:
    Computer Science
    1]What is the use of heuristic functions?

    2]Define artificial intelligence.

    3)How to improve the effectiveness of a search based problem solving technique?

    4]What is a constraint satisfaction problem?

    5]What is a unification algorithm?

    6]How can you represent the resolution in predicate logic?

    7]List out the advantages of nonmonotonic reasoning.

    8]Differentiate between JTMS and LTMS

    9]List out the important components of a script.

    10]What are framesets and instances?

    PART - B (16X5=80)

    11. (a)(i) Give an example of a problem for which breath first search would work better than depth first search.

    (ii). Explain the algorithm for steepest hill climbing.

    OR

    (b). Explain the following search strategies.

    (i) .Best first search

    (ii) .A* search.

    12 .(a) Explain Min Max search procedure

    OR

    (b) .Describe alpha-beta pruning and give the other modifications to the minmax procedure to improve its performance.

    13.. (a) Illustrate the use of predicate logic to represent the knowledge with suitable example.

    OR

    (b) Consider the following sentences:

    John likes all kinds of food.

    Apples are food.

    Chicken is food

    Anything anyone eats and isn't killed alive.

    sue eats everything bill eats

    (i) .Translate these sentences into formulas in predicate logic.

    (ii) .Prove that john likes peanuts using backward chaining

    (iii). Covert the formulas of a part into clause form

    (iv) .Prove tha tjohn likes peanuts using resolution.

    14..(a) With an example explain the logics for nonmonotonic reasoning

    OR

    (b) Explain how Beyesian statistics provides reasoning under various kinds of uncertainty

    15..(a) (i) Construct semantic net representations for th folowing:

    pomepeian (Marcus), Blacksmith ( marcus)

    Mary gave the green flowered vase to her favorite cousin.

    (ii) Construct partitioned semantic net represtations for the following:

    Every batter hit a ball

    All the batters like the pitcher.

    OR

    (b) (i) .Illustrate the learning from examples by induction with suitable examples.
     
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  3. Ankita Katdare

    Ankita Katdare Moderator

    Engineering Discipline:
    Computer Science
    Unit-wise Question Banks:

    UNIT I

    Q1.Give an example of a problem for which breadth-first-search would work better than
depth-first-search would work better than breadth-first-search.


    Q2. describe how the branch-and-bound technique could be used to find the shortest to a
water jug problem.


    Q3. When would best-first-search be worse than simple breadth-first-search ?


    Q5. Write Backward-Chaining Rule System & Forward-Chaining Ruke System.

    Q6.What is default reasoning and how can you perform it with non-monotonic
    reasoning?

    
Q7.What is Logic – Based Truth Maintenance Systems?


    Q8. Explain JTMS and ATMS with proper example.

    
Q9.What is partition semantics Net explain it with example?

    
Q10. What is Mean-End-Analysis ?

    Q11. Write A* algorithm and show how A* algorithm can be used to find minimal-cost
    overall path or simply any path as quickly as possible.


    Q12. How best-first-search algorithm supports heuristic evaluation function?


    Q13.When would best-first-search be worse than simple-first-search ?

    Q14. Find a good heuristic function for following
    (a) Monkey and Banana problem
    (b) Travelling Salesman problem

    Q15. Give an example of an admissible heuristic for the 8-puzzle.

    Q16.Give a heuristic that a block-stacking program might use to solve problems of the
    form ‘stack block X on blockY’. Is the heuristic admissible? Is it monotonic?

    Q17.What is Agenda-Driven Search Algorithm?

    Q18. Show that worst-case algorithm to solve the travelling salesman problem is of exponential complexity but an algorithm that chooser a tour through the nearest neighbour of each city is of lower order. Give an example to show that the best-first- algorithm is not , in general, optimal, but still often good.

    Q19. Discuss some of the potential problems of using hill climbing search. Give an
    examples of the problems cited.


    Q20. Prove that implication is transitive in the prepositional calculas, that is, that
((P->Q) ^ (Q->R) )-> (P -> R)
     
  4. Ankita Katdare

    Ankita Katdare Moderator

    Engineering Discipline:
    Computer Science
    UNIT - II

    Q.1 Discuss the representational structures and knowledge necessary to understand the following sentences.

    The brown dog ate the bone.
    
Attach the large wheel to the axle with the hex nut.

    Mary watered the plants.

    The spirit is willing but the flesh is weak.

    My kingdom for a horse!

    Q2. What are the context-sensitive grammars have a disadvantages for design of practical parsers.

    Q3. What are transition network parser?


    Q4. What is ATN parsers?

    
Q5. What is conceptual dependency?


    Q6. What is Horn Clause and show its implementation in production system?

    
Q7. Write back track algorithm for AND/OR graphs.

    Q8. Write the pseudo-code definition for a bradth-first version of pattern-search. Discuss the time and space efficiency of this algorithm.

    Q9. Is the minmax procedure a depth-first or breadth-first search procedure?

    Q10. Suggest two applications appropriate for solutions using black-board architecture. Briefly characterize the organization of the black-board and knowledge sources for each implementation.

    Q11. What is conceptual Parsing?


    Q12. What are principal advantages of semantic grammar?


    Q13. What are components of natural language understanding process?


    Q14. What is chart parser and explain its use?

    
Q15. What is lexical disambiguation?

    
Q16. What is compositional semantics?


    Q17. Write an ATN grammer that recognizes verb phrases involving auxillary verbs. The
grammer should handle such phrases as
    • “word”
    • “should have gone”
    • “have been going”
    • “would have been going”
    • “would go”
    Do not exact to produce an ATN than can handle all possible verb phrases. But do design one with a reasonable structure that handles most common ones, including the one above. The grammar should create structure that reflects the structure of the input verb phrases.

    Q18. Consider the following sentences:

    Put the red block on the blue block on the table.

    (a) Show all the syntactically valid parsers of this sentence. Assume any standard
    grammatical formalism you like.

    (b) How could semantic information and would knowledge be used to select the appropriate meaning of this command in a particular situation?


    Q19. Consider the problem of providing an English interface to a database of employee records.
    (a) Write a semantic grammar to define a language for this task.
    (b) Show a parse, using your grammar, of each of the two sentences
    What is Smith’s salary
    Tell me who?

    Q20. Explain the main difference between the following three grammars and describe the principal features that could be used to develop specifications for a syntactical recognition program. Consult additional references for more detail regarding each grammar.

    • Chomsky’s Transformational grammar
    • Fillmore’s case grammar

    • Systemic Grammar
     
  5. Ankita Katdare

    Ankita Katdare Moderator

    Engineering Discipline:
    Computer Science
    UNIT-III

    Q1. Write four properties that a good system for knowledge representation in a particular domain should posses.

    Q2. What are issues for knowledge representation?


    Q3. What is inferential knowledge and procedural knowledge?

    
Q4. What is Frame problem?

    
Q5. Consider the following sentences:

    • John likes all kinds of food
    • Apples are food
    • Chicken is food
    • Anything anyone eats and isn’t killed by its food
    • Bill eats peanuts and is still alive
    • Sue eats everything Bill eats

    (a) Translate these sentences into formulas in predicate logic

    (b) Prove that John likes peanuts using backward chaining

    (c) Convert the formulas of part a into clause form

    (d) Prove that John likes peanut using resolution
    
(e) Use resolution to answer the question, “what food does Sue eat?”

    Q6. Assume the following fact:

    • Stove only likes easy courses
    • Sciences courses are hard
    • All the courses in the basket weaving department are easy
    • BK301 is a basket weaving course
Use resolution to answer the question , “what course would Steve like”


    Q7. What is wrong the following argument

    • Men are widely distributed over the earth
    • Socrates is a man
    • Therefore, Socrates is widely distributed over earth
    How should the facts represented by these sentences be represented in logic so that this problem does not arise?

    Q8. A problem-solving search can proceed either forward(from a known start state to desired goal state) or backward (from a goal state to a start state). What factors determine the choice of direction for a particular problem?

    Q9. What search control knowledge?

    Q10. Difference between procedural and declarative knowledge.

    Q11. What are the main advantage in keeping the knowledge base separate from the control module in knowledge – based systems?


    Q12. Under what conditions would it make sense to use both forward and backward chaining ? Give an example where both are used.

    Q13. Explain the difference between forward and backward chaining and under what conditions each would be best to use for a given set of problems.

    Q14. What are the main advantages in keeping the knowledge base separate from the control module in knowledge-based system?

    Q15. Give an example for each of the following types of knowledge
    (a) fact (b) a rule (c) a concept (d) a procedure (e) a heuristic (f) a relationship

    Q16. Give five example of facts that are difficult to represent and manipulate in predicate logic.

    Q17. Difference between semantic Nets and Partitioned Nets.


    Q18. Explain the production rules knowledge base.

    
Q19. What is Minskey Frames?
     
  6. Ankita Katdare

    Ankita Katdare Moderator

    Engineering Discipline:
    Computer Science
    UNIT IV

    Q1. What are characteristic features of expert systems?

    Q2. Write importance of Expert System.


    Q3. Explain the production system inference cycle.


    Q4. What is CASNET? What are its different knowledge types?

    
Q5. What is PIP?


    Q6. Explain Blackboard System Architecture.


    Q7. How knowledge can be structured in a top-to-bottom manner? Explain with example.

    
Q8. What are the feature & capabilities developer should offer in expert system?

    
Q9. What are KEC,OPS5 and Radian Rule Master?


    Q10. How do rules in PROLOG differ from general production system rules?

    Q11. Why is it important that an expert system be able to explains the why and how questions related to a problem solving session?

    
Q12. Give the advantages of expert system architecture based on decision tress over those
of production rules. What are the main disadvantages?

    Q13. Give three examples of applications for which the use of analogical architecture would be suitable in expert system.

    Q14. Explain how uncertainty is propagated through a chain rules during a consultation with an expert system which is based on the MYCIN architecture.

    Q15. Select a problem domain that requires some special expertise and consult with an expert in the domain to learn how he or she solves typical problems.
    After collecting enough knowledge to solve a small subset of problems. Create rules which could be used in a knowledge base to solve the problems. Test the use of the rules on a few problems which have been suggested by the expert and then get his or her confirmation.

    Q16. Obtain a copy of an expert system building tool such as personal consultant Plus and create an expert system to diagnose automobile engine problems. Consult with a mechanic to see if your completed system is reasonably good.

    Q17. Describe and compare the different types of problems solved by four of the earliest expert systems DENDRAL, MYCIN, PROSPECTOR & RI.

    Q18. Identity and describe two good application areas for expert system within a
    university environment.

    Q19. Suppose you are diagonize automobile engine using a system having a frame type of architecture similar to PIP. Show how a trigger condition might be satisfied for the distributed ignition system when it is learned that the spark at all spark
    plugs is weak.

    Q20. Explain why you think associated networks were never very popular forms of
    knowledge representations in expert systems architectures.
     
  7. Ankita Katdare

    Ankita Katdare Moderator

    Engineering Discipline:
    Computer Science
    UNIT V

    Q1. What are the steps of artificial or mechanical recognition?

    Q2. What is conceptual clustering? Write algorithm for conceptual clustering?

    Q3. How speech recognize?

    Q4. Choose three common objects and determine five of their most discriminating visual attributes.

    Q5. Describe how you would design a pattern recognition program which must validate hand written signature. Indentity some potential problem areas.

    Q6. Give two examples where the single representation trick simplifies clustering among unknown objects.

    Q7. Color and texture are both potentially useful in defining regions. Describe an
    algorithm that could be used to determine regions that are homogenous in color.

    Q8. How much memory is required to produced and compare five different binary images , each with a different threshold levels? Assume a system resolution of 512 X 512 . Can the binary images be compressed in some way to reduce memory requirements?

    Q9. What is Marr’s Theory of Vision?

    
Q10. what is ACRONYM System?


    Q11. What is dual – of –edge finding is done?


    Q12.What is Ohta’s Color Scene Analyzer?


    Q13. How low-level processing is done?


    Q14. What is different type of learning?

    
Q15. How is machine learning distinguished from general knowledge acquisition?

    
Q16. Explain why some editors can be distinguished as “intelligent”.


    Q17. Design a learning automaton that selects TV channels based on day of week and
time of day (three evening hours only) for some family you are familiar with.


    Q18. Describe how a learning automaton could be developed to learn how to play the
game of tic-tac-toe optimally. Is this a CLA or simple learning auotomaton system?
     
  8. haslina

    haslina Certified CEan

    Engineering Discipline:
    Computer Science
    • John likes all kinds of food
    • Apples are food
    • Chicken is food
    • Anything anyone eats and isn’t killed by its food
    • Bill eats peanuts and is still alive
    • Sue eats everything Bill eats

    can you explain in prolog languang..iam realy lost n try to understand..but i still can't
     

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