Search Algorithms and Complexity

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Questions and Answers

What must be done if Open is empty during the search algorithm?

Terminate with success

Continue expanding nodes

Return FAIL (correct)

Select another state from closed

Which of the following statements about Depth First Search (DFS) is true?

DFS is complete if there are cycles in the graph.

DFS may get stuck in cycles if visited nodes are not checked. (correct)

DFS is guaranteed to examine every node in the graph.

DFS can find the shortest path to a goal node.

What is a disadvantage of Depth First Search (DFS)?

It may find shorter solution paths first.

It can get too deep into the wrong path. (correct)

It is guaranteed to find a solution.

It examines fewer nodes than Breadth First Search.

What is a key feature of Breadth First Search (BFS)?

BFS finds the best solution in terms of node distance. Signup and view all the answers

In terms of time complexity, what must DFS examine in the worst case?

Every node in the search tree Signup and view all the answers

What happens when cycles exist in a graph for DFS?

DFS may miss the solution altogether. Signup and view all the answers

What is the relation between space and time complexity for both DFS and BFS?

Both have O(bm) space and time complexity. Signup and view all the answers

What does BFS guarantee when finding a solution?

The solution will be the best possible, in terms of shortest path. Signup and view all the answers

Which statement about the expansion of nodes in the search algorithm is correct?

Successors are inserted in Open if they are not in Open or closed. Signup and view all the answers

What should the algorithm do when a goal state is found?

Terminate with success. Signup and view all the answers

What characterizes uninformed search methods?

They operate in a brute force manner without specific strategies. Signup and view all the answers

Which of the following is NOT a criterion for evaluating search strategies?

Performance ratio Signup and view all the answers

What does time complexity in search algorithms refer to?

The number of nodes expanded while finding a solution. Signup and view all the answers

In the context of graph search, what is meant by a 'dead-end'?

A state from which no further progress can be made. Signup and view all the answers

What does the term 'fringe' refer to in search algorithms?

The collection of nodes that have been generated but not yet expanded. Signup and view all the answers

How is 'Big-O' notation primarily used in the evaluation of search algorithms?

To outline asymptotic upper bounds based on various parameters. Signup and view all the answers

Which of the following statements is true regarding the completeness of a search strategy?

Completeness ensures that a solution will be found if it exists. Signup and view all the answers

What is indicated by the 'depth of tree (d)' in the context of evaluating search algorithms?

The longest path from the root to a leaf node within the search tree. Signup and view all the answers

What distinguishes informed search from uninformed search?

Informed search utilizes additional problem-specific knowledge. Signup and view all the answers

What is the first step in the standard outline of a search algorithm?

Initialize: Open ={s} Signup and view all the answers

Study Notes

Evaluating Search Strategies

Completeness: Refers to whether a search strategy guarantees finding a solution if one exists.
Optimality: Determines if the found solution has the lowest cost or the minimum possible cost.
Complexity: Measures the search cost in terms of time and memory required to reach a solution.
- Time complexity: Represents the time taken (number of nodes expanded) to find a solution, considering worst or average cases.
- Space complexity: Measures the space used by the algorithm, indicated by the maximum size of the fringe.

Big-O Notation

Used to compare algorithms.
Defines an asymptotic upper bound based on:
- Depth of the tree (d).
- Average number of branches (b) - also called branch factor.

Uninformed Search

A category of general-purpose search algorithms that use a brute force approach.
Also known as blind search or naïve search.

Outline of Search Algorithm

Initialize: Open set is initialized with the starting state 's'.
Fail: If the Open set becomes empty, the algorithm returns FAIL, indicating no solution found.
Select: A state 'n' is selected from the Open set.
Terminate: If state 'n' is a goal state (n ∈ G), the algorithm terminates successfully.
Expand: Successors of state 'n' are generated using available operators. Each successor 'm' is added to the Open set if it is not already present in Open or Closed sets (m ∉ (Open ∪ Closed)).
Loop: The algorithm returns to step 2.

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Description

This quiz focuses on evaluating search strategies, including their completeness, optimality, and complexity. It covers Big-O notation and uninformed search algorithms, providing insights into their performance and characteristics. Test your understanding of these fundamental concepts in computer science.