a. Illustration of iterative lengthening search algorithm is optimal for the general path costs: Uniform cost just iteratively inspects the unexplored node nearest to the start node. Iterative lengthening search is a uniform cost search that runs multiple times with a growing cost limit from start to finish. The iterative lengthening search has not that much advantage as the iterative deepening search possesses. The weakness of iterative lengthening search: The algorithm simply searches the same node each time and adds more at the ends than the nearest first node and the next closest node are invariant...

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Answer 1

Expert Solution & Answer

Chapter 3, Problem 17E

Explanation of Solution

a.

Illustration of iterative lengthening search algorithm is optimal for the general path costs:

Uniform cost just iteratively inspects the unexplored node nearest to the start node.

Iterative lengthening search is a uniform cost search that runs multiple times with a growing cost limit from start to finish.

The iterative lengthening search has not that much advantage as the iterative deepening search possesses.

The weakness of iterative lengthening search:

The algorithm simply searches the same node each time and adds more at the ends than the nearest first node and the next closest node are invariant...

Explanation of Solution

b.

Number of iterations required for iterative deepening:

The uniform cost search will run through the nodes in the same order as that of the first breadth search.

The search progression will go as follows,

Assume that the goal node is found halfway through the search operation of depth, on average.

Thus the goal iteration = “b+b2+...+bd/2”

Explanation of Solution

c.

Number of iterations required in the worst case:

In the worst case, the limit begins at “0” and increments by a minimum positive cost “ε”, until it reaches the value “d”

Explanation of Solution

d.

Performance of algorithm compared to uniform cost search algorithm:

The algorithm requires only “k” uniform cost searches where iteration simply expands the boundary for the closest nodes inspected...

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Answer 2

Expert Solution & Answer

Chapter 3, Problem 17E

Explanation of Solution

a.

Illustration of iterative lengthening search algorithm is optimal for the general path costs:

Uniform cost just iteratively inspects the unexplored node nearest to the start node.

Iterative lengthening search is a uniform cost search that runs multiple times with a growing cost limit from start to finish.

The iterative lengthening search has not that much advantage as the iterative deepening search possesses.

The weakness of iterative lengthening search:

The algorithm simply searches the same node each time and adds more at the ends than the nearest first node and the next closest node are invariant...

Explanation of Solution

b.

Number of iterations required for iterative deepening:

The uniform cost search will run through the nodes in the same order as that of the first breadth search.

The search progression will go as follows,

Assume that the goal node is found halfway through the search operation of depth, on average.

Thus the goal iteration = “b+b2+...+bd/2”

Explanation of Solution

c.

Number of iterations required in the worst case:

In the worst case, the limit begins at “0” and increments by a minimum positive cost “ε”, until it reaches the value “d”

Explanation of Solution

d.

Performance of algorithm compared to uniform cost search algorithm:

The algorithm requires only “k” uniform cost searches where iteration simply expands the boundary for the closest nodes inspected...

Expert Solution & Answer

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Check out a sample textbook solution

See solution

Answer 3

Expert Solution & Answer

Chapter 3, Problem 17E

Explanation of Solution

a.

Illustration of iterative lengthening search algorithm is optimal for the general path costs:

Uniform cost just iteratively inspects the unexplored node nearest to the start node.

Iterative lengthening search is a uniform cost search that runs multiple times with a growing cost limit from start to finish.

The iterative lengthening search has not that much advantage as the iterative deepening search possesses.

The weakness of iterative lengthening search:

The algorithm simply searches the same node each time and adds more at the ends than the nearest first node and the next closest node are invariant...

Explanation of Solution

b.

Number of iterations required for iterative deepening:

The uniform cost search will run through the nodes in the same order as that of the first breadth search.

The search progression will go as follows,

Assume that the goal node is found halfway through the search operation of depth, on average.

Thus the goal iteration = “b+b2+...+bd/2”

Explanation of Solution

c.

Number of iterations required in the worst case:

In the worst case, the limit begins at “0” and increments by a minimum positive cost “ε”, until it reaches the value “d”

Explanation of Solution

d.

Performance of algorithm compared to uniform cost search algorithm:

The algorithm requires only “k” uniform cost searches where iteration simply expands the boundary for the closest nodes inspected...

Expert Solution & Answer

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Check out a sample textbook solution

See solution

Answer 4

Expert Solution & Answer

Chapter 3, Problem 17E

Explanation of Solution

a.

Illustration of iterative lengthening search algorithm is optimal for the general path costs:

Uniform cost just iteratively inspects the unexplored node nearest to the start node.

Iterative lengthening search is a uniform cost search that runs multiple times with a growing cost limit from start to finish.

The iterative lengthening search has not that much advantage as the iterative deepening search possesses.

The weakness of iterative lengthening search:

The algorithm simply searches the same node each time and adds more at the ends than the nearest first node and the next closest node are invariant...

Explanation of Solution

b.

Number of iterations required for iterative deepening:

The uniform cost search will run through the nodes in the same order as that of the first breadth search.

The search progression will go as follows,

Assume that the goal node is found halfway through the search operation of depth, on average.

Thus the goal iteration = “b+b2+...+bd/2”

Explanation of Solution

c.

Number of iterations required in the worst case:

In the worst case, the limit begins at “0” and increments by a minimum positive cost “ε”, until it reaches the value “d”

Explanation of Solution

d.

Performance of algorithm compared to uniform cost search algorithm:

The algorithm requires only “k” uniform cost searches where iteration simply expands the boundary for the closest nodes inspected...

Expert Solution & Answer

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Check out a sample textbook solution

See solution

Answer 5

Expert Solution & Answer

Answer 6

Expert Solution & Answer

Answer 7

Chapter 3, Problem 17E

Explanation of Solution

a.

Illustration of iterative lengthening search algorithm is optimal for the general path costs:

Uniform cost just iteratively inspects the unexplored node nearest to the start node.

Iterative lengthening search is a uniform cost search that runs multiple times with a growing cost limit from start to finish.

The iterative lengthening search has not that much advantage as the iterative deepening search possesses.

The weakness of iterative lengthening search:

The algorithm simply searches the same node each time and adds more at the ends than the nearest first node and the next closest node are invariant...

Explanation of Solution

b.

Number of iterations required for iterative deepening:

The uniform cost search will run through the nodes in the same order as that of the first breadth search.

The search progression will go as follows,

Assume that the goal node is found halfway through the search operation of depth, on average.

Thus the goal iteration = “b+b2+...+bd/2”

Explanation of Solution

c.

Number of iterations required in the worst case:

In the worst case, the limit begins at “0” and increments by a minimum positive cost “ε”, until it reaches the value “d”

Explanation of Solution

d.

Performance of algorithm compared to uniform cost search algorithm:

The algorithm requires only “k” uniform cost searches where iteration simply expands the boundary for the closest nodes inspected...

Answer 8

Chapter 3, Problem 17E

Explanation of Solution

a.

Illustration of iterative lengthening search algorithm is optimal for the general path costs:

Uniform cost just iteratively inspects the unexplored node nearest to the start node.

Iterative lengthening search is a uniform cost search that runs multiple times with a growing cost limit from start to finish.

The iterative lengthening search has not that much advantage as the iterative deepening search possesses.

The weakness of iterative lengthening search:

The algorithm simply searches the same node each time and adds more at the ends than the nearest first node and the next closest node are invariant...

Answer 9

Chapter 3, Problem 17E

Explanation of Solution

a.

Illustration of iterative lengthening search algorithm is optimal for the general path costs:

Uniform cost just iteratively inspects the unexplored node nearest to the start node.

Iterative lengthening search is a uniform cost search that runs multiple times with a growing cost limit from start to finish.

The iterative lengthening search has not that much advantage as the iterative deepening search possesses.

The weakness of iterative lengthening search:

The algorithm simply searches the same node each time and adds more at the ends than the nearest first node and the next closest node are invariant...

Answer 10

Explanation of Solution

b.

Number of iterations required for iterative deepening:

The uniform cost search will run through the nodes in the same order as that of the first breadth search.

The search progression will go as follows,

Assume that the goal node is found halfway through the search operation of depth, on average.

Thus the goal iteration = “b+b2+...+bd/2”

Answer 11

Explanation of Solution

b.

Number of iterations required for iterative deepening:

The uniform cost search will run through the nodes in the same order as that of the first breadth search.

The search progression will go as follows,

Assume that the goal node is found halfway through the search operation of depth, on average.

Thus the goal iteration = “b+b2+...+bd/2”

Answer 12

Explanation of Solution

c.

Number of iterations required in the worst case:

In the worst case, the limit begins at “0” and increments by a minimum positive cost “ε”, until it reaches the value “d”

Answer 13

Explanation of Solution

c.

Number of iterations required in the worst case:

In the worst case, the limit begins at “0” and increments by a minimum positive cost “ε”, until it reaches the value “d”

Answer 14

Explanation of Solution

d.

Performance of algorithm compared to uniform cost search algorithm:

The algorithm requires only “k” uniform cost searches where iteration simply expands the boundary for the closest nodes inspected...

Answer 15

Explanation of Solution

d.

Performance of algorithm compared to uniform cost search algorithm:

The algorithm requires only “k” uniform cost searches where iteration simply expands the boundary for the closest nodes inspected...

Answer 16

Expert Solution & Answer

Answer 17

Expert Solution & Answer

Answer 18

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Answer 19

Ch. 3 - Explain why problem formulation must follow goal...Ch. 3 - Prob. 2E Ch. 3 - Prob. 3E Ch. 3 - Prob. 4E Ch. 3 - Prob. 5E Ch. 3 - Prob. 6E Ch. 3 - Prob. 8E Ch. 3 - Prob. 9E Ch. 3 - Prob. 10E Ch. 3 - Prob. 11E

Explanation of Solution

Explanation of Solution

Explanation of Solution

c. Number of iterations required in the worst case: In the worst case, the limit begins at “0” and increments by a minimum positive cost “ε”, until it reaches the value “d”

Explanation of Solution

d. Performance of algorithm compared to uniform cost search algorithm: The algorithm requires only “k” uniform cost searches where iteration simply expands the boundary for the closest nodes inspected...

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Chapter 3 Solutions

c.

Number of iterations required in the worst case:

In the worst case, the limit begins at “0” and increments by a minimum positive cost “ε”, until it reaches the value “d”

d.

Performance of algorithm compared to uniform cost search algorithm:

The algorithm requires only “k” uniform cost searches where iteration simply expands the boundary for the closest nodes inspected...