Artificial Intelligence Introduction

Artificial Intelligence Project

Time complexity of DFS will be equivalent to the node traversed by the algorithm. It is given by: , Where, m= maximum depth of any node and this can be much larger than d (Shallowest solution depth).

T(n)=1+n^{2}+n^{3}+....+n^{n}=O(n^{m})

DFS algorithm needs to store only single path from the root node, hence space complexity of DFS is equivalent to the size of the fringe set, which is **O(bm)**.

DFS search algorithm is complete within finite state space as it will expand every node within a limited search tree.

DFS search algorithm is non-optimal, as it may generate a large number of steps or high cost to reach to the goal node.

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