Exam Details
| Subject | artificial intelligence and neural networks | |
| Paper | ||
| Exam / Course | computer science and engineering | |
| Department | ||
| Organization | Vardhaman College Of Engineering | |
| Position | ||
| Exam Date | May, 2018 | |
| City, State | telangana, hyderabad |
Question Paper
VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
B. Tech VI Semester Regular Examinations, May 2018
(Regulations: VCE-R15)
ARTIFICIAL INTELLIGENCE AND NEURAL NETWORKS
(Computer Science and Engineering)
Date: 24 May, 2018 FN
Time: 3 hours
Max Marks: 75
Answer ONE question from each Unit
All Questions Carry Equal Marks
Unit I
1.
State the physical symbol system hypothesis. Explain symbol grounding problem with the Chinese room analogy.
7M
Given an example of a problem for which breadth-first search would work better than depth-first search.
8M
2.
Explain Search technique.
8M
Explain the main steps of hill climbing search algorithm.
7M
Unit II
3.
Explain min-max search procedure with an example.
8M
Illustrate the mapping between facts and representation by considering an English sentence Spot is a dog and fact that all dogs have tails (show deductive mechanism and backward mapping).
7M
4.
Explain the concept of inheritable knowledge in knowledge representation by taking an example.
8M
Briefly explain different sources responsible for gaining efficiency in RETE many-many match algorithm.
7M
Unit III
5.
What is perceptron? Explain the perceptron networks and single perceptron model by taking an example.
7M
Illustrate simplest feedforward network with two layer network having M input units and N output units.
8M
6.
What is ADALINE network? Explain different elements of ADALINE network architecture.
8M
Briefly discuss the Pattern Recognition Problem in artificial neural networks.
7M
Unit IV
7.
Write Hopfield algorithm.
7M
What is the objective of Boltzmann machine and explain the architecture of Boltzmann machine.
8M
8.
Explain the architecture of Bidirectional Associative Memory (BAM).
8M
What is Feed-Forward Neural Networks? Briefly discuss Input, Output, hidden node and layers of Feed-Forward Neural Networks.
7M
Unit V
9.
Describe the components of a planning system.
8M
With a neat diagram explain the expert system architecture.
7M
Cont…2
2
10.
Devise a plan for a robot to clean a kitchen. Consider the following:
i. Cleaning the stove or the refrigerator causes the floor to get dirty
ii. To clean the oven, it is necessary to lock the oven shut and then set the dial to "clean"
iii. Cleaning the refrigerator creates garbage and messes up the counters
iv. Washing the counters or the floor gets the sink dirty
v. Before the floor can be washed, it must be swept
vi. Before the floor can be swept, the garbage must be taken out
Using set of STRIPS-style operator, state the initial state and goal state.
10M
Mention some of the applications of an expert system.
5M
(AUTONOMOUS)
B. Tech VI Semester Regular Examinations, May 2018
(Regulations: VCE-R15)
ARTIFICIAL INTELLIGENCE AND NEURAL NETWORKS
(Computer Science and Engineering)
Date: 24 May, 2018 FN
Time: 3 hours
Max Marks: 75
Answer ONE question from each Unit
All Questions Carry Equal Marks
Unit I
1.
State the physical symbol system hypothesis. Explain symbol grounding problem with the Chinese room analogy.
7M
Given an example of a problem for which breadth-first search would work better than depth-first search.
8M
2.
Explain Search technique.
8M
Explain the main steps of hill climbing search algorithm.
7M
Unit II
3.
Explain min-max search procedure with an example.
8M
Illustrate the mapping between facts and representation by considering an English sentence Spot is a dog and fact that all dogs have tails (show deductive mechanism and backward mapping).
7M
4.
Explain the concept of inheritable knowledge in knowledge representation by taking an example.
8M
Briefly explain different sources responsible for gaining efficiency in RETE many-many match algorithm.
7M
Unit III
5.
What is perceptron? Explain the perceptron networks and single perceptron model by taking an example.
7M
Illustrate simplest feedforward network with two layer network having M input units and N output units.
8M
6.
What is ADALINE network? Explain different elements of ADALINE network architecture.
8M
Briefly discuss the Pattern Recognition Problem in artificial neural networks.
7M
Unit IV
7.
Write Hopfield algorithm.
7M
What is the objective of Boltzmann machine and explain the architecture of Boltzmann machine.
8M
8.
Explain the architecture of Bidirectional Associative Memory (BAM).
8M
What is Feed-Forward Neural Networks? Briefly discuss Input, Output, hidden node and layers of Feed-Forward Neural Networks.
7M
Unit V
9.
Describe the components of a planning system.
8M
With a neat diagram explain the expert system architecture.
7M
Cont…2
2
10.
Devise a plan for a robot to clean a kitchen. Consider the following:
i. Cleaning the stove or the refrigerator causes the floor to get dirty
ii. To clean the oven, it is necessary to lock the oven shut and then set the dial to "clean"
iii. Cleaning the refrigerator creates garbage and messes up the counters
iv. Washing the counters or the floor gets the sink dirty
v. Before the floor can be washed, it must be swept
vi. Before the floor can be swept, the garbage must be taken out
Using set of STRIPS-style operator, state the initial state and goal state.
10M
Mention some of the applications of an expert system.
5M
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