Artificial Intelligence: Search Methods for Problem Solving Week 4 NPTEL Assignment Answers 2025
NPTEL Artificial Intelligence: Search Methods for Problem Solving Week 4 Assignment Answers 2025
1. Paul Valery said “It takes two to invent anything. The one makes up combinations; the other chooses, …… “, What or who does “The one” refer to?
- the scientist in his chemistry lab
- an artist trying out different colours on her canvas
- mixing of genes of two parents in sexual reproduction
- a computer program generating random permutations of a given number
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2. If the genetic makeup of a species/population is not diverse then __________
- then the future generations will be similar to the current one
- the optimum must have been reached
- there may be some good genes that are permanently lost
- when the environment (fitness function) changes the species may not be able to adapt to the change
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3. The fact that in genetic algorithms one can create a new candidate by mixing up parts of two parents means that ____________ .
- each candidate has components that can be swapped with other components to produce a new candidate
- there is hope that some offspring would get good genes from the two parents and become fitter
- one can identify the good genes from prospective parents and create a super child
- all offspring will be better than their parents
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4. In ant colony optimization, _____________ .
- each ant works independently to create a solution by a simple problem solving process
- all the ants collaborate to help each other during the solution building process
- after all the ants have constructed their solution the quality of each solution leaves an imprint on a global strength indicator for each move
- after the first cycle, in the second cycle, all the ants converge to one solution
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5. Conway’s Game of Life, ______________ .
- demonstrates how life forms compete with each other for common resources
- demonstrates the emergence of complexity from simple elements interacting with each other
- demonstrates how simple elements interacting with simple rules can result in a complex composite entity
- demonstrates that life needs energy
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6. Consider chromosomes made of 5-bit binary strings and a fitness function f(a,b,c,d,e) that is a square of (a+4b+6c+4d+e), where “abcde” is a 5-bit chromosome. An initial population is shown in the table.
Fill in the missing values. The actual candidates selected are proportional to the expected number. What are the values of A, B, C, and D? They represent how many copies of the candidate are selected, and will be in the range of 0 to 4.
Enter the values of A,B,C,D as a comma separated list.
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7. In the previous question, the instances selected for crossover are ____________ .
- 00010,00100,10001,00101
- 00010,00010,10001,00101
- 00010,10001,10001,00101
- 00010,00100,00101,00101
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8. Select the valid path representations of the tour.
- A,L,G,E,K,I,B,C,F,J,H,D
- B,I,K,E,G,L,A,D,H,J,F,C
- G,L,A,D,B,I,K,E,H,J,F,C
- A,L,G,C,F,J,H,E,K,I,B,D
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9. The valid adjacency representations of the tour are _____________ .
- D,I,B,H,G,C,L,J,K,F,E,A
- L,C,F,A,K,J,E,D,B,H,I,G
- D,I,G,B,H,C,L,J,K,F,E,A
- L,D,F,A,K,J,C,E,B,H,I,G
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10. Select the ordinal representations of the valid path representations listed in Q8.
- 7,11,1,3,1,5,6,2,3,3,2,1
- 2,8,9,4,5,7,1,2,3,3,2,1
- 5,1,9,6,3,2,6,5,1,2,2,1
- 1,11,6,2,4,6,4,3,4,3,1,1
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11. Path representations of two tours are given below. Generate two offspring using Partially Mapped Crossover, use the locations from 5 to 8 as the mapping segment.
P1: G,L,A,D,B,I,K,E,H,J,F,C
P2: E,A,K,H,D,C,L,J,B,G,I,F
Enter one of the child tours in the text box.
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12. Path representations of two tours are given below. Generate two offspring using Order Crossover, use locations from 5 to 8 as the mapping segment.
P1: G,L,A,D,B,I,K,E,H,J,F,C
P2: E,A,K,H,D,C,L,J,B,G,I,F
In the child tour, place the mapping segment in the middle. For example, C1 = ?,?,?,?,B,I,K,E,?,?,?,?
Enter one of the child tours in the text box.
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13. Path representations of two tours are given below. Generate the two offspring using Cycle Crossover.
P1: G,L,A,D,B,I,K,E,H,J,F,C
P2: E,A,K,H,D,C,L,J,B,G,I,F
Enter one of the child tours in the text box
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14. Path representations of two tours are given below. Compute the ordinal representations of the parent tours and use single point crossover (cut in the middle) to generate the two offspring.
P1: G,L,A,D,B,I,K,E,H,J,F,C
P2: E,A,K,H,D,C,L,J,B,G,I,F
Enter one of the child tours in the text box, use ordinal representation.
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15. The classical single point crossover operator (cut two chromosomes and swap the pieces) used in genetic algorithms when applied on path-representations of two different tours ____________ .
- will produce a tour
- may or may not produce a tour
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16. What is the tour generated by Greedy Heuristic? Use the distance matrix given below.
Enter the path representation of the tour starting from city E.
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17. Starting from city E, what is the tour generated by the Nearest Neighbour Heuristic?
Enter the path representation of the tour starting from city E
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18. Savings heuristic. Use E as the base city, compute the savings list and sort the list in descending order of the savings value.
Enter the top 2 savings values in descending order as a comma separated list.
Answer format: 42,17
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19. Savings heuristic. Continue from the previous question.
Enter the bottom 2 savings values in descending order as a comma separated list.
Answer format: 7,5
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20. Construct the savings tour using E as the base city.
Enter the path representation of the savings tour starting from city E.
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21. Of the three tours (constructed so far) which one has the highest cost?
- The tour generated by the Greedy Heuristic.
- The tour generated by the Nearest Neighbour Heuristic.
- The tour generated by the Savings Heuristic
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