What do mean by Intelligent Agent? Explain the structure of agent in environment with suitable diagram?
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Funda. Of Artificial Intelligence And Machine Learning Questions
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2025 May Jun ENDSEM
2026 Mar INSEM
2025 Mar INSEM
2025 May Jun ENDSEM
2025 Nov Dec ENDSEM
INSEM
2026 Mar INSEM
10 Questions
Q1
15 Marks
Q1
·
b
·
4 Marks
What is PEAS?
Q1
·
c
·
5 Marks
Differentiate between Artificial Intelligent and Machine Learning.
Q2
15 Marks
Q2
·
a
·
5 Marks
What is AI problem? Describe any two AI problems.
Q2
·
b
·
5 Marks
What is meant by AI Turing test? Explain with suitable example
Q2
·
c
·
5 Marks
What is the evolution of artificial intelligence (AI) over time, and what are some of the major applications of AI in various fields and industries?
Q3
15 Marks
Q3
·
a
·
8 Marks
Use the best-first search algorithm to navigate a maze and justify why it is suitable for this type of problem compared to uninformed search methods.
Q3
·
b
·
7 Marks
Implement an online search strategy for a robot navigating an unknown environment and justify the choice of algorithm used.
Q4
15 Marks
Q4
·
a
·
7 Marks
Illustrate how problem reduction can be used to simplify a complex problem like task scheduling in a multi-core processor system.
Q4
·
b
·
8 Marks
Apply a search method with nondeterministic actions to a self-driving car scenario, explaining how it deals with partial observations.
| Subject Name | Funda. Of Artificial Intelligence And Machine Learning |
|---|---|
| Semester | IV |
| Pattern Year | 2019 |
| Subject Code | 218553 |
| Max Marks | 30 |
| Total Questions | 4 |
| Duration | 1 Hour |
| Paper Number | APR-26/SE/Insem-282 |
| Academic Year | S.E. |
| Branch Name | AI & ML |
| Exam Type | INSEM |
| Exam Session | 2026 Mar INSEM |
| Watermark | ['CEGP013091', '152.59.10.40 11/03/2026 13:41:24'] |
INSEM
2025 Mar INSEM
10 Questions
1
15 Marks
1
·
a
·
6 Marks
What do mean by Intelligent Agent? Explain the structure of agent in environment with suitable diagram?
1
·
b
·
4 Marks
What is PEAS?
1
·
c
·
5 Marks
Differentiate between Artificial Intelligent and Machine Learning.
2
15 Marks
2
·
a
·
5 Marks
What is AI problem? Describe any two AI problems.
2
·
b
·
5 Marks
What is meant by AI Turing test? Explain with suitable example.
2
·
c
·
5 Marks
What is the evolution of artificial intelligence (AI) over time, and what are some of the major applications of AI in various fields and industries?
3
15 Marks
3
·
a
·
8 Marks
Explain A* Search Algorithm with example? State advantages and disadvantages of A* Search Algorithm.
3
·
b
·
7 Marks
What is difference between search algorithm and Local search algorithm?
4
15 Marks
4
·
a
·
7 Marks
What is constraint satisfaction problem? Explain back tracking search for CSPs?
4
·
b
·
8 Marks
What is Best First Search Algorithm? What are the advantages of Depth First Search?
| Subject Name | Funda. Of Artificial Intelligence And Machine Learning |
|---|---|
| Semester | IV |
| Pattern Year | 2019 |
| Subject Code | 218553 |
| Max Marks | 30 |
| Total Questions | 4 |
| Duration | 1 Hour |
| Paper Number | [6409]-242 |
| Academic Year | S.E. |
| Branch Name | AI & ML |
| Exam Type | INSEM |
| Exam Session | 2025 Mar INSEM |
| Watermark | ['CEGP013091', '49.248.216.237 12/03/2025 13:42:47 static-237'] |
ENDSEM
2025 May Jun ENDSEM
21 Questions
Q1
18 Marks
Q1
·
a
·
7 Marks
What is knowledge-based agent (KBA) in AI? Explain architecture of KBA with neat diagram?
Q1
·
b
·
6 Marks
Specify the syntax of First-order logic in BNF form with suitable example.
Q1
·
c
·
5 Marks
Compare between Forward Chaining and Backward Chaining.
Q2
18 Marks
Q2
·
a
·
7 Marks
What is the relationship between knowledge and intelligence? Explain various levels of describing knowledge based agent.
Q2
·
b
·
6 Marks
What is Proposition in AI? Explain types of Propositions with example.
Q2
·
c
·
5 Marks
Discuss various approaches of designing a knowledge-based agent.
Q3
17 Marks
Q3
·
a
·
4 Marks
Differentiate between positive class and negative class. Explain the training versus testing phase in machine learning.
Q3
·
b
·
8 Marks
Explain different cross validation techniques.
Q3
·
c
·
5 Marks
Discuss different applications of machine learning.
Q4
17 Marks
Q4
·
a
·
9 Marks
Elaborate various cross validation techniques with advantages and limitations.
Q4
·
b
·
8 Marks
Explain the Machine Learning pipeline in detail with suitable diagram.
Q5
18 Marks
Q5
·
a
·
6 Marks
Compare Supervised, Unsupervised, and Semi-Supervised learning with examples.
Q5
·
b
·
6 Marks
What is the need for Dimensionality Reduction Explain the concept of the Curse of Dimensionality.
Q5
·
c
·
6 Marks
State and justify Real life applications of supervised and unsupervised learning.
Q6
18 Marks
Q6
·
a
·
6 Marks
Explain Principal Component analysis in brief.
Q6
·
b
·
6 Marks
Explain Unsupervised learning with real time examples.
Q6
·
c
·
6 Marks
Write a short note on subset selection.
Q7
17 Marks
Q7
·
a
·
8 Marks
Define following terms: i) Accuracy ii) Precision iii) Recall iv) Error rate
Q7
·
b
·
9 Marks
What is difference between simple linear and multiple linear regressions? Explain how to assessing performance of Regression.
Q8
17 Marks
Q8
·
a
·
9 Marks
Calculate the regression coefficient of X on Y and obtain the lines of regression for the following data X 1 2 3 4 5 6 7 Y 9 8 10 12 11 13 14
Q8
·
b
·
8 Marks
What is an error w.r.t. Regression? Explain at least 4 performance measures for regression.
| Subject Name | Funda. Of Artificial Intelligence And Machine Learning |
|---|---|
| Semester | IV |
| Pattern Year | 2019 |
| Subject Code | 218553 |
| Max Marks | 70 |
| Total Questions | 8 |
| Duration | 2½ Hours |
| Paper Number | [6402]-70 |
| Academic Year | S.E. |
| Branch Name | AI&ML |
| Exam Type | ENDSEM |
| Exam Session | 2025 May Jun ENDSEM |
| Watermark | ['CEGP013091', '49.248.216.237 29/05/2025 09:39:26 static-237'] |
ENDSEM
2025 Nov Dec ENDSEM
20 Questions
Q1
18 Marks
Q1
·
a
·
6 Marks
Discuss various approaches and issues in knowledge representation. Also discuss various problems occur in representing knowledge?
Q1
·
b
·
6 Marks
Expalin the Unification used for reasoning under predicate logic with example.
Q1
·
c
·
6 Marks
Compare between Forward Chaining and Backward Chaining.
Q2
18 Marks
Q2
·
a
·
6 Marks
Explain the algorithm of predicate logic resolution.
Q2
·
b
·
6 Marks
What is reasoning in AI? Explain its types?
Q2
·
c
·
6 Marks
Difference between declarative and procedural knowledge.
Q3
17 Marks
Q3
·
a
·
8 Marks
Explain supervised and unsupervised and reinforcement learning with example.
Q3
·
b
·
6 Marks
Explain the data preprocessing steps in machine learning.
Q3
·
c
·
3 Marks
Distinguish between artificial intelligence and machine learning.
Q4
17 Marks
Q4
·
a
·
4 Marks
Differentiate between positive class and negative class. Explain the training versus testing phase in machine learning.
Q4
·
b
·
8 Marks
Explain different cross validation techniques.
Q4
·
c
·
5 Marks
Discuss different applications of machine learning.
Q5
18 Marks
Q5
·
a
·
9 Marks
Highlighted differences between supervised, unsupervised and semi-supervised learning in machine learning? Explain with examples.
Q5
·
b
·
9 Marks
Define Principal Component Analysis (PCA) and explain how it reduces the dimensionality of data.
Q6
18 Marks
Q6
·
a
·
9 Marks
Define supervised learning and provide real life examples where it is commonly applied.
Q6
·
b
·
9 Marks
Write a short note on Dimensionality reduction.
Q7
17 Marks
Q7
·
a
·
7 Marks
How the performance of Regression is Assessed? Write any four-performance metrics used for Regression.
Q7
·
b
·
10 Marks
Consider the three-class classification matrix. Calculate accuracy, precision and recall per class. Confusion Matrix Predicted A 8 10 1 Actual B 5 60 50 C 3 30 200
Q8
17 Marks
Q8
·
a
·
8 Marks
Define following terms : i) Accuracy ii) Precision iii) Recall iv) Error rate
Q8
·
b
·
9 Marks
What is difference between simple linear and multiple linear regressions? Explain how to assessign performance of Regression.
| Subject Name | Funda. Of Artificial Intelligence And Machine Learning |
|---|---|
| Semester | IV |
| Pattern Year | 2019 |
| Subject Code | 218553 |
| Max Marks | 70 |
| Total Questions | 8 |
| Duration | 2½ Hours |
| Paper Number | [6582]-65 |
| Academic Year | S.E. |
| Branch Name | AI & ML |
| Exam Type | ENDSEM |
| Exam Session | 2025 Nov Dec ENDSEM |
| Watermark | ['CEGP013091', '49.248.216.237 28/11/2025 09:40:46 static-237'] |
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