Iterative deepening depth-first search

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 Iterative deepening depth-first search (IDDFS) is a combination of depth-first search (DFS) and breadth-first search (BFS) algorithms. It is used to find the shortest path in a graph or tree data structure. The algorithm starts with a depth limit of 0 and performs DFS up to that limit. If the goal state is not found, the depth limit is increased, and the search is repeated until the goal state is found.

The IDDFS algorithm works by performing a series of DFS with increasing depth limits until the goal state is found. It starts by performing DFS with a depth limit of 0. If the goal state is not found, the algorithm increases the depth limit by 1 and repeats the DFS from the root node. The process is repeated until the goal state is found or the maximum depth limit is reached.

IDDFS has the advantages of both DFS and BFS. It is complete like BFS since it explores all possible nodes at each depth before moving on to the next level. It is also memory-efficient like DFS since it only needs to store the current path and not the entire search tree. IDDFS is optimal if the cost of each action is non-negative.

IDDFS is commonly used in applications where the search space is too large to explore completely and the optimal solution is not known. It is often used in game-playing, artificial intelligence, and natural language processing applications.

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