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The document outlines an assignment for a course in Artificial Intelligence, detailing tasks across multiple units. Key topics include major AI task domains, search algorithms like A* and MiniMax, predicate logic, Bayesian networks, and neural networks. Additionally, it includes programming tasks in Prolog and discussions on genetic algorithms and natural language processing.

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25 views2 pages

Assignment

The document outlines an assignment for a course in Artificial Intelligence, detailing tasks across multiple units. Key topics include major AI task domains, search algorithms like A* and MiniMax, predicate logic, Bayesian networks, and neural networks. Additionally, it includes programming tasks in Prolog and discussions on genetic algorithms and natural language processing.

Uploaded by

solankivrajesh451
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as PDF, TXT or read online on Scribd
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Department of Computer science and engineering

Artificial Intelligence (3170716)


Assignment
==================================================================
Unit 1:
• Enlist and discuss major task domains of Artificial Intelligence.
Unit 2:
• Explain Water Jug problem with Sate Space Search method.
• What is A* search? Explain various stages of A* search with an example
• Discuss with example: Constraint Satisfaction Problem
Unit 3:
 Explain cut and Fail predicate
 Differentiate forward chaining and backward chaining with suitable example
Unit 4:
 Consider the following sentences:
• Raj likes all kinds of food.
• Apples are food.
• Anything anyone eats and isn’t killed by is food.
• Sachin eats peanuts and is still alive.
• Vinod eats everything Sachin eats. Now, attempt following:
i. Translate these sentences into formulas in predicate logic.
ii. Use resolution to answer the question, “What food does Vinod eat?”
 Define Non monotonic reasoning.
Unit 5:
 State the Bayes theorem. Illustrate how a Bayesian Network can be used to represent
causality relationship among attributes.
Unit 6:
• Explain the MiniMax search procedure for Game Playing. Also explain alpha and
Beta cut-offs to improve the performance of MinMax procedure.
Unit 7:
• Explain the components of planning system.
Unit 8:
• Enlist and describe different phases/steps involved in Natural Language Processing.
Unit 9:
• Short not on Perceptron and Artificial Neural Network
• Explain Backpropagation algorithm in Neural Network
• Explain supervised and unsupervised learning
Unit 10:
● Draw and explain architecture of Expert System.
Unit 11:
● Explain about the basic operators in genetic algorithms.
Unit 12:
● Write following prolog programs: 1) To find factorial of a given number. 2) To find the
nth element of a given list.

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