Artificial Intelligence
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
2080-new
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 question.
Define state space graph. Differenciate between A* search and greedy best first search.
What do you mean by unification and lifting ? Convert following sentences into FOPL
Sushma likes all kinds of practical courses.
AI and DBMS are practical courses.
Any subject anyone practices is practical course.
Ruby practices PHP.
Rita practices everything that Ruby practices.
Using resolution check whether “Sushma likes PHP” is inferred or not.
Differentiate supervised learning from unsupervised? Discuss how Naïve Bayes Model can be used for machine learning ? Support your answer with example.
SECTION B
Attempt any EIGHT question.
How can you define AI from the dimension of behavioural process? When a machine is said to pass Turing Test?
What is an agent ? How utility agent works? Give an example of utility agent.
What is game search? How minmax search used in game playing ? Illustrate with an example.
What is semantic network? Given following knowledge base, represent it using semantic network
Subash is a student. All students are person. Person has hair. Ram is a player.All player play game. Game is a physical action. Height of all players is larger than the height of all student. Physical action starts fron 7:00 AM and ends at 9:00 AM.
Discuss how genetic algorithm works?
Using your own assumptions, design PEAS framework for following intelligent agents.
a. Medicine delivery drone
b. Covid medicine prescriber.
What is machine vision? Describe the components of machine vision.
How natural language generation differs from natural language understanding ? How morphological analysisis done in NLP ?
What is constraint satisfaction problem? Illustrate graph coloring problem as constraint satisfaction problem.