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NPTEL Fundamentals of Artificial Intelligence Assignment
ABOUT THE COURSE :
What does automatic scheduling or autonomous driving have in common with web search, speech recognition, and machine translation? These are complex real-world problems that span across various practices of engineering! Aim of artificial intelligence (AI) is to tackle these problems with rigorous mathematical tools. The objective of this course is to present an overview of the principles and practices of AI to address such complex real-world problems. The course is designed to develop a basic understanding of problem solving, knowledge representation, reasoning and learning methods of AI.
Next Week Assignment Answers
This course can have Associate in Nursing unproctored programming communication conjointly excluding the Proctored communication, please check announcement section for date and time. The programming communication can have a weightage of twenty fifth towards the ultimate score.
- Assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
- ( All assignments in a particular week will be counted towards final scoring – quizzes and programming assignments).
- Unproctored programming exam score = 25% of the average scores obtained as part of Unproctored programming exam – out of 100
- Proctored Exam score =50% of the proctored certification exam score out of 100
UNPROCTORED PROGRAMMING EXAM SCORE >=10/25 AND PROCTORED EXAM SCORE >= 20/50.
BELOW YOU CAN GET YOUR NPTEL Fundamentals of Artificial Intelligence Assignment 1 Answers 2022? :
Q1. Aristotle was one of the firsts to attempt to codify “thinking”. His _________ provided patterns of argument structure that always gave correct conclusions, given correct premises
2. Turing test or Imitation Game, was put forth as a simple test that could be used to _______
A. prove machines could think.
B. break the enigma code.
C. show human are intelligent.
D. show machines can compute.
3. Overall computational cost of a AI Production System is in two major categories: Rule Application Cost and Control Strategy Cost. For an Uninformed Control System, we have the following:
A. Low Rule Application Cost and High Control Strategy Cost
B. Low Rule Application Cost and Low Control Strategy Cost
C. High Rule Application Cost and Low Control Strategy Cost
D. High Rule Application Cost and High Control Strategy Cost
4. For more complex games, such as chess or checker the AND/OR search to termination is out of question. Which of the following statements are true?
I. Our goal in searching such a game tree might be, instead, merely to find a good first move.
II. Extract from the search graph an estimate of the ‘best’ first move.
A. Both I and II.
B. Only II
C. Only I
D. Both I and II are false.
5. For Breadth First Search, the following statements are correct
A. Fringe is a FIFO queue
B. Fringe is a LIFO queue
C. Deepest node is expanded first.
D. Nodes are added to the front of the OPEN list.
6. Bidirectional search is a graph search algorithm that runs two simultaneous searches. Which of the following statements is false for bidirectional search? .
A. Requires the ability to generate predecessor states.
B. Bidirectional search is always optimal.
C. Stop when the frontiers intersect.
D. Works well only when there are unique start and goal states
7. There are two distinct specialized production systems; Order in which a set of applicable rules is applied to a database is unimportant for a ________ production system.
D. AND/ OR
8. To solve a problem using a production system, one must specify __________________
A. The Global database, Rules and Control Strategy
B. Some search technique
C. Initial facts only
9. __________ aims at building machines that act intelligently, without taking a position on whether or not the machines actually are intelligent.
A. Weak AI
B. Strong AI
C. Connectionist AI
D. Symbolic AI
10. The AO* algorithm can best be seen as the following TWO major operations:
A. Step I: Top-down: graph-growing; Step II: Bottom-up: cost-revising, SOLVE-labelling.
B. Step I: Bottom-up: graph-growing; Step II: Top-down: cost-revising, SOLVE-labelling.
C. Step I: Top-down: graph-growing, SOLVE-labelling; Step II: Bottom-up: cost-revising.
D. Step I: Bottom-up: graph-growing, SOLVE-labelling; Step II: Top-down: cost-revising.