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Gtu Paper Pyqs

This document outlines the examination details for the 'Fundamentals of Artificial Intelligence' subject at Gujarat Technological University, scheduled for November 28, 2024. It includes instructions for the exam, a breakdown of questions covering various AI topics such as search algorithms, game playing, knowledge representation, fuzzy sets, and neural networks. The total marks for the exam are 70, and students are allowed to use simple scientific calculators.

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108 views2 pages

Gtu Paper Pyqs

This document outlines the examination details for the 'Fundamentals of Artificial Intelligence' subject at Gujarat Technological University, scheduled for November 28, 2024. It includes instructions for the exam, a breakdown of questions covering various AI topics such as search algorithms, game playing, knowledge representation, fuzzy sets, and neural networks. The total marks for the exam are 70, and students are allowed to use simple scientific calculators.

Uploaded by

ram8401180438
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
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Enrolment No.

/Seat No_______________

GUJARAT TECHNOLOGICAL UNIVERSITY


BE- SEMESTER–V (NEW) EXAMINATION – WINTER 2024
Subject Code:3154202 Date:28-11-2024
Subject Name:Fundamentals of Artificial Intelligence
Time:10:30 AM TO 01:00 PM Total Marks:70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
4. Simple and non-programmable scientific calculators are allowed.

Marks
Q.1 (a) List various application domain of Artificial Intelligence with 03
suitable example.
(b) Discuss the role of Agents and Environments in Artificial 04
Intelligence.
(c) Compare and contrast Breadth first search and Depth first 07
Search, highlighting major advantages and disadvantages.

Q.2 (a) List key challenges in Game playing with suitable example. 03
(b) Elaborate the role of Adversial search, in Game playing with 04
suitable example.
(c) Discuss Mini-max algorithm, with relevant features and
highlightinh 07
applications.
OR
(c) Define Alpha-Beta pruning and its relevance for AI applications 07
in detail.

Q.3 (a) List key approaches to Knowledge Representation using Rules. 03


(b) Explain the role of Logic Programming with the help of suitable 04
example.
(c) Compare and contrast Procedural Versus Declarative 07
Knowledge, highlighting key features and limitations.
OR
Q.3 (a) Discuss the Certainty Factors and Rule- Base Systems in brief. 03
(b) Explain the working of Non-Monotonic Reasoning with the help 04
of suitable example.
(c) Differentiate between Forward versus Backward Reasoning 07
highlighting key features and limitations.

Q.4 (a) List key operations of fuzzy set with suitable example. 03
(b) Discuss Membership function and its key features in detail. 04
(c) Compare and contrast supervised learning and unsupervised 07
learning, highlighting key features and limitations.
OR
Q.4 (a) Explain conventional set with suitable example. 03
1
(b) How Evaluation and Cross Validation is significant, discuss with 04
example.
(c) Compare and contrast Linear Regression and K-nearest 07
Neighbour, highlighting key features and limitations.

Q.5 (a) Discuss key features of Biological Neural Networks. 03


(b) How Activation Functions works, discuss in detail. 04
(c) Compare and contrast Perceptron NN and Multilayer Perceptron 07
NN, highlighting key features and limitations.
OR
Q.5 (a) Discuss the key features of Artificial Neural Networks. 03
(b) How Semantic Analysis is helpful, explain in detail. 04
(c) Illustrate the Discourse and Pragmatic Processing with suitable 07
diagram.

*************

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