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• Min-Max search algorithm explores best paths using depth-first-search(DFS) and backtracking techniques. Constant increase and decrease of utilities by our user against AI makes all that fun.
• Uses alpha‑beta pruning to decrease the number of nodes that are evaluated by the min‑max algorithm in its space tree making the AI efficient. Time complexity in best case reduces to O(B^(D/2)) from O(B^D).
• Implementing a SMART AI CHESS game using the above two algorithms will be fun:)
