The course introduces the ideas and techniques underlying the principles and design of artificial intelligent systems. The course covers the basics and applications of AI including: design of intelligent agents, problem solving, searching, knowledge representation systems, probabilistic reasoning, neural networks, machine learning and natural language processing.
Tribhuvan University
Institute of Science and Technology
Ai Model Qn
Bachelor Level / fourth-semester / Science
Computer Science and Information Technology( CSC266 )
Artificial Intelligence
Full Marks: 60 + 20 + 20
Pass Marks: 24 + 8 + 8
Time: 3 Hours
Candidates are required to give their answers in their own words as far as practicable.
The figures in the margin indicate full marks.
Section A
Attempt any two questions.
What do you mean by heuristic search? Given following state space representation, show how greedy best firsh and A* search is used to find the goal state.
S is the start state and G is the goal state. The heuristics of the states are:
h(S) = 12, h(A)=8, h(D)=9, h(B)=7, h(E)= 4, h(C)=5, h(F)=2, h(G)=0.
How resolution algorithm is used as a rule of inference in predicate logic? Convert the following sentences into FOPL.
Prove that “Roney is naughty” using resolution algorithm.
What is artificial neural network? Define its mathematical model. Discuss how back propagation algorithm is used to train ANN.
Section B
Attempt any eight questions.
Describe how Turing test is used to define AI as acting humanly.
Differentiate between model based and simple reflex agent with an example.
What is natural language processing? Discuss the steps of natural language processing.
How belief networks are constructed? Consider the probability of having cloudy is 50%. The probability that it will rain given the conditions it will be cloudy and if it is winter is 30%. The probability of being winter is 50%. The probability that it will be shin is 70%. Now construct a belief network for this example.
What is expert system? Explain the major components of expert system.
What is supervised learning? Discuss how Naive Bayes model works.
Construct semantic network for following facts
Ram is person. Persons are humans. All human have nose. Humans are instances of mammals. Ram has weight of 60 kg. Weight of Ram is less than weight of Sita.
How min-max algorithm is used in game search? For the following state space, show how min-max algorithm finds path for the two players.
Construct a PEAS framework for following intelligent agents.
a. Internet Shopping Assistant
b. English Language Tutor.
