Podcast
Questions and Answers
What must be done if Open is empty during the search algorithm?
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?
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)?
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)?
What is a key feature of Breadth First Search (BFS)?
In terms of time complexity, what must DFS examine in the worst case?
In terms of time complexity, what must DFS examine in the worst case?
What happens when cycles exist in a graph for DFS?
What happens when cycles exist in a graph for DFS?
What is the relation between space and time complexity for both DFS and BFS?
What is the relation between space and time complexity for both DFS and BFS?
What does BFS guarantee when finding a solution?
What does BFS guarantee when finding a solution?
Which statement about the expansion of nodes in the search algorithm is correct?
Which statement about the expansion of nodes in the search algorithm is correct?
What should the algorithm do when a goal state is found?
What should the algorithm do when a goal state is found?
What characterizes uninformed search methods?
What characterizes uninformed search methods?
Which of the following is NOT a criterion for evaluating search strategies?
Which of the following is NOT a criterion for evaluating search strategies?
What does time complexity in search algorithms refer to?
What does time complexity in search algorithms refer to?
In the context of graph search, what is meant by a 'dead-end'?
In the context of graph search, what is meant by a 'dead-end'?
What does the term 'fringe' refer to in search algorithms?
What does the term 'fringe' refer to in search algorithms?
How is 'Big-O' notation primarily used in the evaluation of search algorithms?
How is 'Big-O' notation primarily used in the evaluation of search algorithms?
Which of the following statements is true regarding the completeness of a search strategy?
Which of the following statements is true regarding the completeness of a search strategy?
What is indicated by the 'depth of tree (d)' in the context of evaluating search algorithms?
What is indicated by the 'depth of tree (d)' in the context of evaluating search algorithms?
What distinguishes informed search from uninformed search?
What distinguishes informed search from uninformed search?
What is the first step in the standard outline of a search algorithm?
What is the first step in the standard outline of a search algorithm?
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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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