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Questions and Answers
What does the solution to a search problem consist of?
What is the root of a search tree in the context of a search problem?
Which function assigns a numeric cost to each path in a search problem?
What type of search guarantees that a solution has the lowest cost among all solutions?
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In heuristic search, what is used to traverse the search space?
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Which technique involves traversing the search space until the goal node is found, and might involve exhaustive search?
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What is the sequence of actions that transforms the start state to the goal state in a search problem called?
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Which component of a search problem gives the description of all available actions to the agent?
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In a search problem, what is used to represent a tree structure showing all possible states and transitions?
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Which search technique involves traversing the search space with applied rules and can use techniques like Greedy Best First Search and A* Algorithm?
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What guarantees that a solution found in search has the lowest cost compared to all other solutions?
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What function assigns a numeric cost to each path in a search problem?
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Study Notes
Search Problem in Artificial Intelligence
- A search problem consists of a state space, start state, goal test, and solution.
- State space is a set of all possible states where you can be.
- Start state is the state from where the search begins.
- Goal test is a function that determines whether the current state is the goal state.
- Solution is a sequence of actions, called the plan, that transforms the start state to the goal state.
Search Problem Components
- Search tree: a tree representation of the search problem, with the root node corresponding to the initial state.
- Actions: descriptions of all available actions to the agent.
- Transition model: a description of what each action does, represented as a transition model.
- Path cost: a function that assigns a numeric cost to each path.
- Solution: an action sequence that leads from the start node to the goal node.
- Optimal solution: a solution with the lowest cost among all solutions.
Search Techniques
- Heuristic search: traverses the search space with applied rules (information).
- Techniques: Greedy Best First Search, A* Algorithm.
- Blind search: traverses the search space until the goal node is found (might be exhaustive).
- Techniques: Breadth First, Depth First, Depth Limited, Iterative Deepening, Uniform Cost search.
- Blind search guarantees a solution, while heuristic search does not.
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Description
Test your knowledge on the components of a search problem in Artificial Intelligence. Learn about state space, start state, goal test, and solution sequence. Explore the concept of a search tree in problem-solving.
