Search algorithms are one of the most important areas of Artificial Intelligence. This topic will explain all about the search algorithms in AI.
Search: Searchingis a step by step procedure to solve a search-problem in a given search space. A search problem can have three main factors:Search Space: Search space represents a set of possible solutions, which a system may have. Start State: It is a state from where agent begins the search. Goal test: It is a function which observe the current state and returns whether the goal state is achieved or not.
Search tree: A tree representation of search problem is called Search tree. The root of the search tree is the root node which is corresponding to the initial state.
Actions: It gives the description of all the available actions to the agent.
Transition model: A description of what each action do, can be represented as a transition model.
Path Cost: It is a function which assigns a numeric cost to each path.
Solution: It is an action sequence which leads from the start node to the goal node.
Optimal Solution: If a solution has the lowest cost among all solutions..
Completeness: A search algorithm is said to be complete if it guarantees to return a solution if at least any solution exists for any random input.
Optimality: If a solution found for an algorithm is guaranteed to be the best solution (lowest path cost) among all other solutions, then such a solution is said to be an optimal solution.
Time Complexity: Time complexity is a measure of time for an algorithm to complete its task.
Space Complexity: It is the maximum storage space required at any point during the search, as the complexity of the problem.
For More details: Search Algorithms in AI - Javatpoint