AI || pre board Short Answer 2022

7th semester

Asian ,ims ,orchid ,prime


  1. When machine is termed intelligent in Turing Test?

In 1950,machine is termed intelligent in Turing Test.

  1. What are the four ways to evaluate the performance of searching?
    • Completeness
    • Optimality
    • Time complexity
    • Space complexity


  1. Define fuzzy set and crisp set.

Elements are allowed to be partially included in the fuzzy set. i.e., A Fuzzy Set has Fuzzy Boundaries.
A crisp set is an unordered collection of different elements. So we can say that crisp set has exact boundary.

  1. What is recognize act cycle?

The recognize-act cycle implements search allowing the production system to move towards a goal within the set of rules.

  1. What are the problems in hill climbing search?
    • Local Maximum
    • Plateau
    • Ridges


  1. What is meant by neural network?

An Artificial Neural Network (ANN) is an information processing paradigm(model) that is inspired by the way biological nervous systems process information.

  1. What is knowledge representation? List any two knowledge representation techniques.

Knowledge representation is the part of Artificial intelligence which concerned with AI agents thinking and how thinking contributes to intelligent behavior of agents.

  • Logical Representation
  • Semantic Network Representation
  • Frame Representation
  • Production Rules


  1. Define disjunctive normal form.

Disjunctive normal form (DNF) is the normalization of a logical formula in Boolean mathematics. In other words, a logical formula is said to be in disjunctive normal form if it is a disjunction of conjunctions with every variable and its negation is present once in each conjunction.

  1. What is the function of inference engine in expert system?

The role of the inference engine is to deduce, starting from input facts, some other facts, either intermediate or final output, using the encoded rules.

  1. What do you mean by stochastic learning?

Stochastic refers to a variable process where the outcome involves some randomness and has some uncertainty.


  1. Determine whether the given condition statement is true or false. Give reason. If 2+2=5, then dogs can fly.
  • 2+2=5 =F
  • Dog can fly =F
  • IfF F     Then it is True
  1. Define laws of thought approach.
  • The laws of thoughtare fundamental axiomatic rules upon which rational discourse itself is often considered to be based. The formulation and clarification of such rules have a long tradition in the history of philosophy and logic. Generally they are taken as laws that guide and underlie everyone’s thinking, thoughts, expressions, discussions, etc. However, such classical ideas are often questioned or rejected in more recent developments, such as intuitionistic logic, dial theism and fuzzy logic.
  1. Define crisp set in fuzzy logic
  • Crisp setsare the sets that we have used most of our life. In a crisp set, an element is either a member of the set or not. … Fuzzy sets, on the other hand, allow elements to be partially in a set. Each element is given a degree of membership in a set.
  1. What are the 4R of case base reasoning?
  • retrieve,
  • reuse,
  • revise and
  • retain
  1. Define CNF with suitable example
  • Conjunctive normal form (CNF) is an approach to Boolean logicthat expresses formulas as conjunctions of clauses with an AND or O Each clause connected by a conjunction, or AND, must be either a literal or contain a disjunction, or OR operator. CNF is useful for automated theorem proving.


  1. Differentiate between supervised and unsupervised learning
supervised unsupervised
In this the output for the given input is known
It is a predictive modeling technique which predict the future outcome accurately
It includes classification and regression algorithm
In this the outcome for the given input is unknown
It is the description modeling technique which explains the real relationship between the elements and history of the elements
It includes clustering and association rule learning algorithms


  1. Why single layer perceptron cannot learn XOR?
  • A “single-layer” perceptron can’timplement XOR. The reason is because the classes in XOR are not linearly separable. You cannot draw a straight line to separate the points (0,0),(1,1) from the points (0,1),(1,0).
  1. What is meant by agent’s percept sequence?
  • An agent’s percept sequenceis the complete history of everything that the agent has ever perceived.



  • Rationality Is Nothing But Status Of Being Reasonable, Sensible, And Having Good Sense Of Judgment. It Is Differ From Intelligence Because Intelligence As “Ability To Efficiently Achieve Goals In A Wide Range Of Domains”, While Instrumental Rationality Is Defined As “The Art Of Choosing And Implementing Actions That Steer The Future Toward Outcomes Ranked Higher In One’s Preferences”.
  • If An Agent’s Current State And Selected Action Can Completely Determine The Next State Of The Environment, Then Such Environment Is Called A Deterministic A StochasticEnvironment Is Random In Nature And Cannot Be Determined Completely By An Agent.
  • A Search Algorithm Is Said To Be Complete If It Guarantees To Return A Solution If At Least Any Solution Exists For Any Random Input.
  • Game PlayingIs Minimax Search It Is Depth-First Depth-Limited Search Procedure.Where As A Heuristic Is A Technique To Solve A Problem Faster Than Classic Methods, Or To Find An Approximate Solution When Classic Methods Cannot. This Is A Kind Of A Shortcut As We Often Trade One Of Optimality, Completeness, Accuracy, Or Precision For Speed.
  • Conflict Resolution StrategiesAre Used In Production Systems In Artificial Intelligence, Such As In Rule-Based Expert Systems, To Help In Choosing Which Production Rule To Fire. The Need For Such A Strategy Arises When The Conditions Of Two Or More Rules Are Satisfied By The Currently Known Facts.
  • Supervised LearningIs The Machine Learning Task Of Learning A Function That Maps An Input To An Output Based On Example Input-Output Pairs. It Infers A Function From Labeled Training Data Consisting Of A Set Of Training
  • No It Is Not Possible To Develop Expert System If The Domain Expert Does Not Have The Computer Programming Knowledge.
  • PEAS Stands For Performance Measures, Environment, Actuators, And Sensors.
  • NLUGenerates Facts From NL By Using Various Tools And Techniques, Such As POS Tagger, Parsers, And So On, In Order To Develop NLP Applications. NLG Start From Facts Like POS Tags, Parsing Results, And So On To Generate The NL. It Is The Process Of Reading And Interpreting Language.
  • Crisp Logic(Crisp) Is The Same As Boolean Logic(Either 0 Or 1). Either A Statement Is True(1) Or It Is Not(0), Meanwhile Fuzzy LogicCaptures The Degree To Which Something Is True.



1.What is a rational agent?
=>Rational agent always does right thing based upon its prior knowledge, percept history, its ability and its constraints like time and space limitation. A rational agent must be able to learn and be autonomous. It always act to maximize its expected value.
2.What is the theme of Chinese room argument?
=> The point of the argument is this: if the man in the room does not understand Chinese on the basis of implementing the appropriate program for understanding Chinese then neither does any other digital computer solely on that basis because no computer, qua computer, has anything the man does not have.

  1. What is fuzzification?

=>  Fuzzification is the process of converting a crisp input value to a fuzzy value that is    performed by  the use of the information in the knowledge base.

  1. Explain supervised learning with example

=> In Supervised learning, you train the machine using data which is well “labeled.” It means some data is already tagged with the correct answer. It can be compared to learning which takes place in the presence of a supervisor or a teacher.

  1. What is plateau problem?

=> This is an area where the search space is flat so that all neighbors return the same evaluation. On plateau all neighbors have same value. Hence, it is not possible to select the best direction.

  1. Define modus tollens.

=> In propositional logicmodus tollens  is a valid argument form and a rule of inference. It is an application of the general truth that if a statement is true, then so is its contrapositive.

  1. When is A* search optimal?

=> A* search gives optimal solution when the heuristic function is admissible heuristic.

  1. What is rule based system?

=> A  rule-based system is a set of “if-then” statements that uses a set of assertions, to which rules on how to act upon those assertions are created.

  1. Explain semantic network with an example.

=> A semantic network is a graphic notation for representing knowledge in patterns of interconnected nodes. An example of a semantic network is WordNet, a lexical database of English.

  1. What is reinforcement learning?

=> Reinforcement learning is an area of Machine Learning. It is about taking suitable action to maximize reward in a particular situation. It is employed by various software and machines to find the best possible behavior or path it should take in a specific situation.